Browse Topic: Unmanned ground vehicles

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IMPLEMENTATION OF THE 4D/RCS ARCHITECTURE WITHIN THE SOUTHWEST SAFE TRANSPORT INITIATIVE2024-01-3086To be published on 11/15/2027
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer.
McWilliams, George, Brown, Michael
OMNI-DIRECTIONAL AUTONOMOUS GUIDED VEHICLE (AGV) WITH WIRELESS NAVIGATION2024-01-343611/15/2024
ABSTRACT Automatic guided vehicles (AGV) have made big inroads in the automation of assembly plants and warehouse operations. There are thousands of AGV units in operation at OEM supplier and service facilities worldwide in virtually every major manufacturing and distribution sector. Although today’s AGV systems can be reconfigured and adapted to meet changes in operation and need, their adaptability is often limited because of inadequacies in current systems. This paper describes a wireless navigated (WN) omni-directional (OD) autonomous guided vehicle (AGV) that incorporates three technical innovations that address the shortfalls. The AGV features consist of: 1) A newly developed integrated wireless navigation technology to allow rapid rerouting of navigation pathways; 2) Omnidirectional wheels to move independently in different directions; 3) Modular space frame construction to conveniently resize and reshape the AGV platform. It includes an overview of the AGVs technical features and how the flexibility and agility can be adapted to fit military and commercial application. The AGV is being evaluated as a mobile work station platform and a precise material handling robot.
Cheok, Ka C, Radovnikovich, Micho, Fleck, Paul, Hallenbeck, Kevin, Grzebyk, Steve, Vanneste, Jerry, Ludwig, Wolfgang, Garner, Robert
Unmanned Systems (UxS) Control Segment (UCS) Architecture: Architecture DescriptionAS6512A (Historical)7/14/2020
This document is the Architecture Description (AD) for the SAE Unmanned Systems (UxS) Control Segment (UCS) Architecture Library Revision A or, simply, the UCS Architecture. The architecture is expressed by a library of SAE publications as referenced herein. The other publications in the UCS Architecture Library Revision A are: AS6513A, AS6518A, AS6522A, and AS6969A.
AS-4UCS Unmanned Systems Control Segment Architecture
Control Model of Automated Driving Systems Based on SOTIF Evaluation2020-01-12144/14/2020
In partially automated and conditionally automated vehicles, a part of the work of human drivers is replaced by the system, and the main source of safety risks is no longer system failures, but non-failure risks caused by insufficient system function design. The absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or by reasonably foreseeable misuse by persons, is referred to as the Safety Of The Intended Functionality. Drivers have the responsibility to supervise the automated driving system. When they don't agree with the operation behavior of the system, they will interfere with the instructions. However, this may lead to potential risks. In order to discover the causes of human misuse, this paper takes the trust feeling between the driver and the automated driving system as the starting point, and based on the collected data of track test, establishes the evaluation indicator -- degree of confidence to show the trust feeling between the driver and the automated system. Degree of confidence is a comprehensive interpretation of the driver's physical and psychological feelings. In the process of track test, we simultaneously collect the dynamics indicators of the vehicle. After the test, the drivers' driving feeling was evaluated by questionnaire. Then, the relationship between objective indicator and subjective score was established by machine learning method, and the development of evaluation indicator was completed. Finally, this paper optimizes the automatic driving motion planning algorithm based on this indicator, and verifies the effectiveness of the algorithm through simulation.
Guo, Mengge, Shang, Shiliang, Haifeng, Cui, Zhang, Kaijiong, Deng, Weishun, Zhang, Xi, Yu, Fan
Analysis of LiDAR and Camera Data in Real-World Weather Conditions for Autonomous Vehicle Operations2020-01-00934/14/2020
Autonomous vehicle technology has the potential to improve the safety, efficiency, and cost of our current transportation system by removing human error. With sensors available today, it is possible for the development of these vehicles, however, there are still issues with autonomous vehicle operations in adverse weather conditions (e.g. snow-covered roads, heavy rain, fog, etc.) due to the degradation of sensor data quality and insufficiently robust software algorithms. Since autonomous vehicles rely entirely on sensor data to perceive their surrounding environment, this becomes a significant issue in the performance of the autonomous system. The purpose of this study is to collect sensor data under various weather conditions to understand the effects of weather on sensor data. The sensors used in this study were one camera and one LiDAR. These sensors were connected to an NVIDIA Drive Px2 which operated in a 2019 Kia Niro. Two custom scenarios (static and dynamic objects) were chosen to collect sensor data operating in four real-world weather conditions: fair, cloudy, rainy, and light snow. An algorithm developed herein was used to provide a method of quantifying the data for comparison against the other weather conditions. The results from these performance algorithms show that sensor data quality degrades by an average of 13.88% for static objects and 16.16% for dynamic objects while operating in these conditions, with operations in rain proving to have the most significant effect on sensor data degradation. From this study, it is hypothesized that advancements in data processing algorithms can improve the usability of this degraded data. In future work, we seek to explore fault-tolerant sensor fusion algorithms that can overcome the effects of adverse weather.
Goberville, Nick, El-Yabroudi, Mohammad, Omwanas, Mark, Rojas, Johan, Meyer, Rick, Asher, Zachary, Abdel-Qader, Ikhlas
Decision Making and Trajectory Planning for Lane Change Control Inspired by Parallel Parking2020-01-01344/14/2020
Lane-changing systems have been developed and applied to improve environmental adaptability of advanced driver assistant system (ADAS) and driver comfort. Lane-changing control consists of three steps: decision making, trajectory planning and trajectory tracking. Current methods are not perfect due to weaknesses such as high computation cost, low robustness to uncertainties, etc. In this paper, a novel lane changing control method is proposed, where lane-changing behavior is analogized to parallel parking behavior. In the perspective of host vehicle with lane-changing intention, the space between vehicles in the target adjacent lane can be regarded as dynamic parking space. A decision making and path planning algorithm of parallel parking is adapted to deal with lane change condition. The adopted algorithm based on rules checks lane-changing feasibility and generates desired path in the moving reference system at the same speed of vehicles in target lane. Compared to algorithm for static parking space, the uncertainty of the space between moving vehicles and host vehicle dynamics raises stricter requirements for algorithms. Works are conducted to deal with dynamically changing scenarios, such as design of safety zone and exit conditions to avoid collision. Simulation under PreScan-Simulink environment shows that the proposed method outperforms in lane change scenarios and achieves strong robustness to inter-vehicle dynamics.
Yu, Liangyao, Ru, Ze, Lu, Zhenghong, Liang, Guanqun, Xiong, Cenbo, Lanie, Abi, Wang, Ruyue
Reconciling Simultaneous Evolution of Ground Vehicle Capabilities and Operator Preferences2020-01-01724/14/2020
An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers. We consider this utility distribution as the prior and update it to a posterior with feedback that can be acquired from actual system use. The framework improves the utility function and thereby the decisions made for the next generation systems, allowing continuous improvement. We present our approach on a ground vehicle selection problem.
Slon, Christopher, Pandey, Vijitashwa, Gorsich, David, Jayakumar, Paramsothy
Lithium-Ion Battery Cell Modeling with Experiments for Battery Pack Design2020-01-11854/14/2020
Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters. The model validation is performed by experimental discharging voltage curves and cell surface temperature data. Simulated data matches the experiments with acceptable discrepancy. As a cell is the building block to form high-voltage battery module and pack, the developed cell model could play an important role in battery pack development and design.
Liu, Yiqun, Liao, Y. Gene, Lai, Ming-Chia
Parameter Estimation of Non-Paved Roads for ICVs Using 3D Point Clouds2020-01-50212/24/2020
Road parameter estimation is important for intelligent and connected vehicles (ICVs) operating on non-paved roads as it may influence their path planning and motion control. This paper presents a method for the estimation of longitudinal slopes, lateral slopes, and roughness of non-paved roads using 3D point clouds. Firstly, the regions of interest (ROIs) of ground are extracted by rasterizing the point clouds with grids, and divided into blocks according to the densities of point clouds. Next, longitudinal and lateral slopes are estimated by calculating the angles between two preference planes fitted using Random Sample Consensus (RANSAC) and Least Squares. Finally, an index of roughness, which is similar to International Roughness Index (IRI), is proposed for road roughness estimation in different grids. Experimental tests on non-paved roads demonstrate that the proposed algorithm has satisfactory performance in terms of the estimation accuracy of road slopes and roughness.
Kangjian, Yan, Manjiang, Hu, Dongsheng, Wang, Xiaowei, Wang, Guotao, Xie
Robot Performs Complex ManeuversTBMG-358301/1/2020
At a height of less than a foot, Salto (saltatorial locomotion on terrain obstacles) the robot can vault over three times its height in a single bound. First introduced in 2016, Salto now can bounce in place and jump through obstacle courses, potentially leaping through rubble to aid in search-and-rescue missions.
Helping Autonomous Vehicles See Around CornersTBMG-357601/1/2020
To improve the safety of autonomous systems, MIT engineers have developed a system that can sense tiny changes in shadows on the ground to determine if there’s a moving object coming around the corner.
Apollo 11 History Archive Helps Virtual Reality Program Come to LifeTBMG-347417/1/2019
Spinoff is NASA’s annual publication featuring successfully commercialized NASA technology. This commercialization has contributed to the development of products and services in the fields of health and medicine, consumer goods, transportation, public safety, computer technology, and environmental resources.
Localization and Mapping of Unknown Locations with Unmanned Ground Vehicles19AERP05_095/1/2019
Developing a commercial off-the shelf (COTS) software platform to enable UGVs to navigate and survive in complex environments. Army Engineer Research and Development Center, Vicksburg, Mississippi The main goals of this research are to enhance a commercial off-the-shelf (COTS) software platform to support unmanned ground vehicles (UGVs) exploring the complex environment of tunnels, to test the platform within a simulation environment, and to validate the architecture through field-testing. In this research, software was designed and tested for a UGV in order to give it the capability to localize and map an unknown area while navigating. The UGV was equipped with a camera, acoustic sensor, and a laser range finder that provides the UGV with readings to determine its pose and landmarks within the unknown area to create a map of the unknown research.
The CAN Bus: Driving the Future of Autonomous Military Vehicles19AERP05_025/1/2019
It's a crisp November day in Michigan, and a convoy of British and American resupply vehicles are rumbling along at a comfortable 25 miles per hour. In the lead is a British Army Rheinmetall MAN Military Vehicles (RMMV) HX-60 truck, trailed closely by two U.S. Army Oshkosh Light Medium Tactical Vehicles (LMTVs). In total, there are zero humans operating this convoy. This was the scene in November 2017, when the US-UK Coalition Assured Autonomous Resupply (CAAR) demonstration took place at Camp Grayling, Michigan - the result of three years of research and engineering to examine the use of unmanned ground vehicles (UGVs) in resupply situations, to tackle so-called “last mile” issues regarding supplying troops on the front lines of active conflicts around the world.
Miniature Bearings Play a Major Role in Mars 2020 MissionTBMG-343925/1/2019
Timken North Canton, OH
Aerospace & Defense Technology: May 201919AERP055/1/2019
Autonomous "Wingman" Vehicles The Future of Military Unmanned Vehicle Technology The CAN Bus: Driving the Future of Autonomous Military Vehicles Underwater Drone Technology Eyes In the Sky For Drones, Combining Vision Sensor and IMU Data Leads to More Robust Pose Estimation Hydraulic Cylinder Position Sensor Technology Ensuring precision movement in robotic assemblies. Geospatial Accuracy of Small Unmanned Airborne System Data in the Coastal Environment Determining the performance of image processing software could lead to better data collection strategy. Monitoring a Nearshore Beneficial Use Site: Application of a Benthic Sled and Video Annotation Passive survey method provides less labor and resource intensive system for monitoring the effects of dredging on aquatic life in nearshore beneficial use sites. Developing Knowledge and Understanding for Autonomous Systems for Analysis and Assessment Events and Campaigns An effort to overcome the challenges involved in developing complete performance ontologies and test methodologies for evaluating the performance of autonomous systems. Localization and Mapping of Unknown Locations with Unmanned Ground Vehicles Developing a commercial off-the shelf (COTS) software platform to enable UGVs to navigate and survive in complex environments. Sound Attenuation of Neoprene Wetsuit Hoods as a Function of Dive Depth and Acoustic Frequency: Hyperbaric Chamber Trials Data gathered during testing will help develop strategies to protect Navy divers from loud underwater sounds.
Localization and Mapping of Unknown Locations with Unmanned Ground VehiclesTBMG-343405/1/2019
The main goals of this research are to enhance a commercial off-the-shelf (COTS) software platform to support unmanned ground vehicles (UGVs) exploring the complex environment of tunnels, to test the platform within a simulation environment, and to validate the architecture through field- testing.
The CAN Bus: Driving the Future of Autonomous Military VehiclesTBMG-343435/1/2019
It’s a crisp November day in Michigan, and a convoy of British and American resupply vehicles are rumbling along at a comfortable 25 miles per hour. In the lead is a British Army Rheinmetall MAN Military Vehicles (RMMV) HX-60 truck, trailed closely by two U.S. Army Oshkosh Light Medium Tactical Vehicles (LMTVs). In total, there are zero humans operating this convoy.
Evaluation of Navigation in Mobile Robots for Long-Term Autonomy in Automotive Manufacturing Environments2019-01-05054/2/2019
In recent times, a number of reference implementations of Simultaneous Localization and Mapping (SLAM) and navigation techniques have been made publicly available via the ROS Community. Several implementations have transitioned to commercial products (vacuum robots, drones, warehouse robots, etc.). However, in such cases, they are specialized and optimized for their specific domains of deployment. In particular, their success criteria have been based primarily on mission completion and safety of humans around them. In this light, deployment in any new operational design domain (ODD) requires at least a careful verification of performance and often re-optimization. We seek the technological gaps that need to be addressed to ensure the mobile robots are fit for automotive manufacturing environments. Automotive final assembly environments pose significant additional challenges for mobile robot deployment. They are replete with relatively unstructured tasks with significant uncertainty, involve tasks with skills that require robots to work in collaboration with humans and are time sensitive. Currently, metrics for evaluating mobile robot functionalities have been based on accuracy, functionality and resource consumption. In addition to these, automotive assembly also requires consistency in execution times. This work evaluates the navigational capabilities of mobile robots in environments with static objects for time consistency as required by an automotive assembly process. The evaluation uses ASTM F3244-17 standard test method. It is performed on a simulated robot in Gazebo environment and Clearpath OTTO1500 robot in a laboratory environment.
Singh Gill, Jasprit, Tomaszewski, Mark, Jia, Yunyi, Pisu, Pierluigi, Krovi, Venkat N
Training of Neural Networks with Automated Labeling of Simulated Sensor Data2019-01-01204/2/2019
While convolutional neural networks (CNNs) have revolutionized ground-vehicle autonomy in the last decade, this class of algorithms requires large, truth-labeled data sets to be trained. The process of collecting and labeling training data is tedious, time-consuming, expensive, and error-prone. In order to automate this process, an automated method for training CNNs with simulated data was developed. This method utilizes physics-based simulation of sensors, along with automated truth labeling, to improve the speed and accuracy of training data acquisition for both camera and LIDAR sensors. This framework is enabled by the MSU Autonomous Vehicle Simulator (MAVS), a physics-based sensor simulator for ground vehicle robotics that includes high-fidelity simulations of LIDAR, cameras, and other sensors.
Goodin, Chris, Sharma, Suvash, Doude, Matthew, Carruth, Daniel, Dabbiru, Lalitha, Hudson, Christopher
Parameters Analyses and Identification for Rubber Bush Based on Theoretical Dynamic Model with Effects of Temperature and Preload2019-01-12724/2/2019
A series connection of the KVBC (Kelvin-Voigt and Bouc-wen) theoretical model of rubber bush in automobile suspension is established. The numerical calculation model is also developed through Matlab/simulation and 9 parameters are identified. Experiments are conducted on the rubber bush on a bench for dynamic and static characteristics and to supply appropriate and reliable data for parameter identification. Based on this, preload and temperature are taken into consideration in an ordinary KVBC model as two important additional factors. As a result, it leads to developing a novel model with new parameter identification, which is validated under different conditions. This new modeling method of rubber bush has three advantages. First, it shows improved accuracy for solving non-linear problems in a multi-body calculation, which is useful for researchers and vehicle engineers. In addition, this new method leads to a very important step for choosing appropriate bush model type before analysis, which depends on the preload value. Furthermore, the model can be used to handle real situations with temperature variation around rubber bushes during simulation, which has been studied for many years for automobile NVH performance versus temperature.
He, Rong, Zhou, Hong
XPONENTIAL 2019 – An AUVSI ExperienceTBMG-341364/1/2019
The Association for Unmanned Vehicle Systems International (AUVSI) is bringing this year's XPONENTIAL 2019 to McCormick Place in Chicago, IL. The event, which runs from April 29 – May 2, will feature more than 150 technical sessions focused on all aspects of the unmanned vehicle and robotics market. Over 700 exhibitors representing more than 20 different industries will be showcasing their latest technology to an estimated 8,500 attendees from all over the world.
Walking Robot Moves Without GPSTBMG-338702/27/2019
Ants are able to use polarized light and ultraviolet radiation to locate themselves in space. AntBot mimics this ability to explore its environment randomly and go home automatically, without GPS or mapping.
Simulation Optimization of the NASA Mars Fuel In-Situ Resource Utilization and Its Infrastructure2018-01-196310/30/2018
The National Aeronautics and Space Administration’s (NASA) current objectives include expanding space exploration and planning a manned expedition to Mars. In order to meet the latter objective, it is imperative that humans generate their own products by harnessing space resources, a process referred to as In-Situ Resource Utilization (ISRU). ISRU will enable NASA to reduce both payload mass and mission cost by reducing the number of consumables required to be launched from Earth. The discrete-event simulation discussed focuses primarily on one ISRU system, the production of fuel for a return trip to Earth by utilizing Mar’s atmosphere and regolith. This ISRU system primarily uses autonomous rovers for exploration, excavation, processing of Mar’s regolith to produce fuel, and disposal of the processed regolith. This study explores individual rover and component requirements including rover speeds, travel distances, functional periods, charging, and maintenance times. The interactions of these individual components are highly interdependent and was evaluated to determine how they affect the overall ISRU system behavior, other components, and system requirements. By creating a simulation, the requirements and viability of the fuel ISRU system is now able to be evaluated and analyzed as a basis for planning and designing strategies. This study then aims to optimize uptime and number of different rovers required to reduce mission cost while still meeting fuel requirements. In addition, special efforts were given to improve visuals and animations to represent the process and to better communicate the Mars fuel ISRU requirements to a variety of audiences.
Vezina, Ashley, Coutts, Lindsey, Cohen, Emily, Burns, David
Technique Allows Mobile Robots to Navigate AutonomouslyTBMG-3307710/1/2018
A technique was developed to quickly teach robots novel traversal behaviors with minimal human oversight. The technique allows mobile robot platforms to navigate autonomously in environments while carrying out actions a human would expect of the robot in a given situation.
Coating Erosion Tests Help Keep Mars 2020 Rover SafeTBMG-328479/1/2018
Air Force Research Laboratory (AFRL) Wright-Patterson Air Force Base, OH
Autonomous Crop-Counting RobotTBMG-324728/1/2018
Today's crop breeders are trying to boost yields while preparing plants to withstand severe weather and changing climates. To succeed, they must locate the genes for high-yielding, hardy traits in crop plants’ DNA, a task that is needed to accelerate breeding to meet global food demand.
A Preliminary Systems Engineering Study on a Concept for Mars Exploration with an Unmanned Autonomous Vehicle and Ground RoverF-0074-2018-126835/14/2018
ABSTRACT Exploration of Mars has been one of the focus of the aerospace community for its similarity with the Earth. The characteristics of Mars make possible an aerial flight even with the low pressure in its atmosphere. In an age where the ground rover exploration is dominant, the addition of a rotary-wing unmanned autonomous vehicle (UAV) would expand the exploration possibilities, increasing the range and the amount of scientific data collected. In this work, it is shown a conceptual systems design that combines a rotary-wing UAV and a ground rover in collaboration, for the exploration of the terrain. The work was developed in the Systems Engineering level of conceptualization and Design phase. Subsequent Computer-Aided-Design (CAD), Finite Element Analysis (FEA) and Rapid Prototyping were performed as well in this study.
Lacerda, Michel, Park, Dongjin, Patel, Srujal, Schrage, Daniel
Development of a Vision-Based Situational Awareness Capability for Unmanned Surface VesselsTBMG-289095/1/2018
Using unmanned surface vessels (USVs) for “dull, dirty and dangerous missions” is gaining traction in recent years as it removes the human element from a potentially life-threatening environment in missions such as mine hunting or maritime interdiction. Current USVs rely on human operators sitting in remote control stations to monitor the vessels’ surroundings and perform collision detection and avoidance. This reliance on the human operator constrains the operating envelope of the USV as it requires a high bandwidth and low latency communication link for safe operations, especially in waters with heavy traffic.
Soldier-Robot Team Communication: An Investigation of Exogenous Orienting Visual Display Cues and Robot Reporting PreferencesTBMG-289035/1/2018
The advancement of robot capabilities and functionality has changed the way in which soldiers perform many of their operational tasks. The various unmanned air, ground, and submersible vehicles currently deployed have significantly impacted present-day warfare.
A Comprehensive Testing and Evaluation Approach for Autonomous Vehicles2018-01-01244/3/2018
Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap. In this paper, firstly a three-dimensional evaluation model conforming to the functional architecture of autonomous vehicles was built, with each dimension representing one of the three key functional layers of autonomous vehicle including sensing & perception, decision-making ﹠ planning, control & execution. Each dimension has a set of metrics carefully defined with their weights fairly determined based on an entropy weights method. Then, considering environment effect on vehicle functions, we innovatively determine task-scenarios for testing the performance of each dimension. Besides, we design a hierarchical systematic testing method which could specially testing each function layer of autonomous vehicle. Fuzzy comprehensive and TOPSIS evaluation method was proposed to quantitatively evaluate the comprehensive performance of autonomous vehicles under defined task-scenarios. Finally, our methods are used to evaluate three candidate vehicles based on simulation scenario in PanoSim. Compared to traditional approach based on external task performance, the proposed approach can not only provide convincing results of the overall system performance but can also peek into each of the key functional layer and provide insights about their performance. Therefore, this approach provides better guidance for autonomous vehicle research.
Wang, Guojun, Deng, Weiwen, Zhang, Sumin, Wang, Jinsong, Yang, Shun
Optimal Torque Allocation for Distributed Drive Electric Skid-Steered Vehicles Based on Energy Efficiency2018-01-05794/3/2018
Steering of skid-steered vehicles without steering mechanism is realized by differential drive/brake torque generated from in-wheel motors at left and right sides. Compared to traditional Ackerman-steered vehicles, skid-steered vehicles consume much more energy while steering due to greater steering resistance. Torque allocation is critical to the distributed drive skid-steered vehicles, since it influences not only steering performance, but also energy efficiency. In this paper, the dynamic characteristics of six-wheeled skid-steered vehicles were analyzed, and a 2-DOF vehicle model was established, which is important for both motion tracking control and torque allocation. Furthermore, a hierarchical controller was proposed. Considering tire force characteristics and tire slip, the upper layer calculates the generalized force and desired yaw moment based on anti-windup PI (proportion-integral) control method. On the fundamental of dynamic characteristics of skid-steered vehicles and electric motor efficiency characteristics, the lower layer utilizes different optimal torque allocation strategies based on energy efficiency at different driving conditions, namely, straight line driving condition and steering condition. The control results show that the motion controller can track the reference yaw rate accurately and at the same time much energy can be saved by proposed torque allocation strategy.
GAO, Letian, Xiong, Lu, Gao, Xiang, Yu, Zhuoping
2021-12-29.TEST Design and Implementation of Adaptive Range LIDAR System (ARLS) for Autonomous Braking Assistance at High Speeds in Automobiles2018-01-00404/3/2018
Autonomous braking systems are prevalent in mid/upper-mid range vehicles today. The major drawback: acute boundary condition during which the system will function. The paper describes the implementation of Adaptive Range LIDAR Systems (ARLS) containing a state of the art collimator and wave shaper with a 140̊ sweep MEMS mirror, capable of calculating beam convergence as a function of distance, considering multiple obstacles ahead of it. The paper also describes the use of ARLS for ACC (Adaptive Cruise Control) and Autonomous braking, reinforcing the available software structure with more data points. Contrary to the other systems that detect objects/obstacles from a stationary point of reference, ARLS determines the velocity of obstacle with respect to the ground point of reference and computes most optimum brake effort curve. The brake curves are alike for every situation, as it is dynamic in nature, hence, additional electronics ensure physical curve tracing by manipulating the braking circuitry, or in some vehicles, by providing feedback to the Electronic Brakeforce Distribution Systems. Also, since the brake effort curve is dynamic with respect to time, rigorous braking is not imposed on the passenger, and that the retardation is smooth and well distributed in time.
Mishra, Jainendra
AUREATE: An Augmented Reality Test Environment for Realistic Simulations2018-01-10804/3/2018
Automated driving is currently one of the most active areas of research worldwide. While the general progress in developing specific algorithms for perception, planning and control tasks is very advanced, testing and validation of the resulting functions is still challenging due to the large number of possible scenarios and generation of ground-truth. Currently, real world testing and simulations are used in combination to overcome some of these challenges. While real world testing does not suffer from imperfect sensor models and environments, it is expensive, slow and not accurately repeatable and therefore unable to capture all possible scenarios. However, simulation models are not sophisticated enough to fully replace real world testing. In this paper, we propose a workflow that is capable of augmenting real sensor-level data with simulated sensor data. With this approach we are able to generate scenarios which are as realistic as possible while also being flexible with the ability to insert arbitrary objects. This sensor-level based approach enables testing of the whole algorithm chain for automated driving, including perception, object-detection, scene understanding, path planning, decision making, and control.
Koduri, Tejaswi, Bogdoll, Daniel, Paudel, Shreyasha, Sholingar, Gautham
Study on a Fuzzy Q-Learning Approach Using the Driver Priori Knowledge for Intelligent Vehicles’ Autonomous Navigation and Control2018-01-10844/3/2018
The functional elements of decision making system are fuzzy, adaptive and self-learning for intelligent ground vehicles. As is well-known, operating environment of unmanned ground vehicles (UGVs) is complex, unknown and time-changing. And on the other hand, exact dynamic model of the vehicle is relatively difficult to gain. However, the changing of special dynamic parameters and the man-made driving laws of velocities and running direction are easily available. Therefore, this paper attempts to provide an approach based on fuzzy Q-learning algorithm for studying autonomous navigation and control system’s design, which aims to make unmanned vehicles adaptive and robust under complex and time-changing environment. The presented approach utilizes the drivers’ empirical knowledge for. Fuzzy inference system introduces the human beings’ successful experiences into the system, and Q-learning mainly pays more attention to the interaction between the robot and the environment and thus keeps on learning until achieving the goal. Through this method, autonomous navigation and control system can be designed accordingly. This paper used a type of the nonholonomic robotic system for the computational experiments so as to verify the algorithm, which only considers necessary candidate conclusions. The final simulation results show the validity of the designed algorithm. The presented algorithm is not dependent on the dynamic model, and is designed in terms of the special model parameters. Therefore, the mentioned approach has strong versatility and transplantable, which can be easily used for penetration maneuver strategies and autonomous maneuver of other type of intelligent vehicles such as unmanned aerial vehicles (UAVs) or autonomous underwater vehicles (AUVs).
Chang, Liang, Bai, Jie, Huang, Liangbo
Crab Crawl Maneuver for Independently Steerable Wheeled PlatformsTBMG-2780211/1/2017
An industrial-class excavator was developed for use on the Moon and perhaps on Mars. The model mobility platform uses Ackerman Steering with active drives on all six wheels, and steering on the corners. A faulty sequence of wheel steering and driving commands resulted in undocumented behaviors in a simulation and rendering program that appear to have actual applicability to surface operations. Quite by accident, it was discovered that by applying power and steering to the wheels in a complex pattern, the excavator could move laterally, hard to starboard. The intended command was “reverse,” and the execution was a seemingly random turning and driving of all of the simulated six wheels. The faulty behavior was employed to remove the robotic platform when it was stuck on rocks, and enabled the platform to “scoot” side-ways, successfully disentangling from the rocks. The method drove the wheels in the direction of the intended motion, while steering them in a sweeping motion, and the apparent motion resembles swimming.
Using Thermal Simulation to Model the Effects of Wind on the Mars Curiosity RoverTBMG-2766010/1/2017
The Centro de Astrobiología (CAB), a joint center of Consejo Superior de Investigaciones Cientificas and the Instituto Nacional de Tecnica Aeroespacíal (CSIC-INTA), designed and built the weather monitoring station contributed by the Spanish government as part of the payload of the Mars Science Laboratory (MSL) rover, Curiosity, which landed on Mars in August 2012 (Figure 1).
A Guide for Developing Human-Robot Interaction Experiments in the Robotic Interactive Visualization and Experimentation Technology (RIVET) Simulation17AERP05_105/1/2017
Using computer gaming technology to improve the interaction between humans and unmanned ground vehicles. Army Research Laboratory, Aberdeen Proving Ground, Maryland ARL's Intelligent Systems Enterprise vision is to enable the teaming of autonomous intelligent systems with soldiers in dynamic, unstructured combat environments, as well as in noncombat military installations and base operations. To accomplish this vision for interdependent soldier-robot teaming, there has been a paradigm shift in robotic research conducted by ARL from the current instantiation of fielded remote-controlled or teleoperated robots to systems with increased intelligence, decision-making capability, and autonomy. This type of teaming is needed for future joint, interdependent, network-enabled operations. While the technological capabilities of robotic systems are advancing by the day, many of these new systems are still in the early stages of research and development. In many cases, areas of need or potential use have been identified, preliminary requirements have been created, and engineering solutions for prototype systems have been researched. However, the human element must be considered early on in this design process, because without considering human factors, such as human-system interfaces, performance, as well as trust and expectation, the potential result will be limited or inappropriate use of the system.
Military system designers aren't resting on COTS deployment17TOFHP04_074/1/2017
As ground vehicles employ more electronic sensing, control and communication systems, design engineers are increasingly utilizing more commercial off-the-shelf (COTS) modules. Though COTS slashes development time and cost, it's still difficult for many military users to find COTS boards that meet their low-volume demands for ruggedization and redundancy. Sensing and computing systems in vehicles get more complex, so there's increased interest in modules based on the VME and Open VPX, a successor to the venerable VME bus, created by the VITA Trade Association, according to several speakers at the recent Embedded Tech Trends conference. More military projects are adopting open architectures that offer a number of production-ready computing and sensing boards.
Costlow, Terry
Obstacle Avoidance Strategy and Implementation for Unmanned Ground Vehicle Using LIDAR2017-01-01183/28/2017
Regarding safety, obstacle avoidance has been considered as one of the most important features among ADAS systems for ground vehicles. However, the implementation of obstacle avoidance functions to commercial vehicles are still under progress. In this paper, we demonstrate a complete process of obstacle avoidance strategy for unmanned ground vehicle and implement the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was used to detect the obstacles on the fore-path. Based on the measured LIDAR data, an optimized path is automatically generated with accommodation of current car position, obstacle locations, car operation capability and global environmental restrictions. The path planning is updated in real time while new or changing obstacles being detected. This algorithm is validated by the simulation results with the RC car. The comparison will be discussed at the end of this paper. The successful implementation of the proposed strategy demonstrates the feasibility of this obstacle avoidance methodology, which can be applied to commercial autonomous vehicle.
Wang, Yang, Goila, Ankit, Shetty, Rahul, Heydari, Mahdi, Desai, Ambarish, Yang, Hanlong
Generalized Query Tool for Accessing the Database of the Mars Relay Operations Service (MaROS)TBMG-263642/1/2017
The Generalized Query Tool for accessing the database of MaROS can be utilized in three modes: (1) batch mode where a user's authentication data is inserted directly along with a desired query to the database, (2) interactive mode where a desired query is known and can be entered directly, and (3) interactive mode with a query “wizard” that walks a user through the steps needed to construct a valid query to the database. In all three cases, the successful execution of the script results in data from the MaROS database being made available to the user in a comma-separated output file. For new users, it is recommended to use the third mode to build a sample query and then tailor that as desired for use with the first or second modes.
Mars Science Laboratory ChemCam Sun SafetyTBMG-261861/1/2017
The Mars Science Laboratory (MSL) ChemCam instrument can be damaged when the Sun enters or passes through its field of view (FOV). There is no Sun cover, yet other instruments mounted with boresights pointing in the same direction must observe the Sun for scientific observations and for attitude determination. When in a Suntolerant focus range during rover motion and pointing for observations by other remote sensing instruments, the Sun must be allowed to pass through the ChemCam FOV, and when in a Sun-damage focus range for ChemCam observations, the Sun must never be allowed to enter the FOV, even after a rover system fault. Both of these scenarios depend upon knowledge of the attitude of the rover relative to the motion of the Sun. A Sun search that is guaranteed to be Sun-safe for the ChemCam, even when the location of the Sun is unknown, had to be developed.
Streams: A Hyper-Responsive Telemetry Interaction Tool on the WebTBMG-2605112/1/2016
JPL Operations Engineers (Operators) need to interact with their telemetry to assess the health of and successfully operate a spacecraft or rover. Operators must analyze the immediate data for health and understand the current state of these complex systems, but they also must be able to evaluate the long-term engineering data to identify trends and potential pitfalls that develop over time. Whether starting with long-term trends or short-term data, operators have large amounts of data and need a tool so that their expertise is spent analyzing the data and trends, rather than working to tease these trends from outdated toolsets not equipped to handle large data sets. Existing tools pre-compute either long-term trends or short-term plots, but further ad-hoc analysis is prohibitively difficult, can take many hours per query, and queries necessitate either special access or that the operator be on a specific network to access data and to correlate it to models.
Estimation of Excavator Manipulator Position Using Neural Network-Based Vision System2016-01-81229/27/2016
A neural network-based computer vision system is developed to estimate position of an excavator manipulator in real time. A camera is used to capture images of a manipulator, and the images are down-sampled and used to train a neural network. Then, the trained neural network can estimate the position of the excavator manipulator in real time. To study the feasibility of the proposed system, a webcam is used to capture images of an excavator simulation model and the captured images are used to train a neural network. The simulation results show that the developed neural network-based computer vision system can estimate the position of the excavator manipulator with an acceptable accuracy.
Xu, Jiaqi, Yoon, Hwan-Sik, Lee, Jae Y., Kim, Seonggon
Elimination of Yaw Component of Gyroscope Propagation Error During Arm Activity in MSLTBMG-253249/1/2016
When updating attitude during arm motion, gyroscope propagation error soon becomes greater than the tilt being monitored. The solution is to add an accelerometer-only mode that can update attitude without using gyroscopes, and to add the ability to monitor pitch and roll separately. Accelerometer-only mode is used only when it is safe to assume that any vehicle shifting in yaw would also be accompanied by shifting in pitch and/or roll. For surface contact operations, it is important to monitor change in tilt of the vehicle resulting from arm motion.
Algorithm Helps Lunar Rover Move Through ClutterTBMG-250517/1/2016
Today’s robots easily execute “pick-and-place” tasks: finding an object in one specified location and bringing it to another. But what if there are obstacles in a robot’s way? And what if the machine is on uncertain terrain, like the surface of the Moon?
AutoNav: Navigation Flight Software on a SmartphoneTBMG-249447/1/2016
Today’s mobile computing platforms (phones and tablets) contain considerable computing power and are instrumented similar to spacecraft. They have cameras, accelerometers, gyros, magnetometers, GPS, and multiple radios for communication. It was postulated that a modern commercial smartphone could make an excellent test platform for spacecraft flight software.
Aerospace & Defense Technology: May 201616AERP055/2/2016
UAV Technology Using SWaP-C Reductions to Improve UAS/UGV Mission Capabilities UGV Technology Designing Rugged Computing Platforms for UGVs UUV & Robotics Technology Bi-manual Dexterous Manipulation for Maritime Explosive Ordnance Disposal UUV Technology Applying UUV Advances to Safeguard Harbors and Littoral Waters Robotics Technology Designing a Robot to Counter Vehicle-Borne Improvised Explosive Devices
RF System MATLAB Model Simulation Using a Variety of Data SourcesTBMG-245275/1/2016
During the development of the Soil Moisture Active-Passive (SMAP) High-Power Amplifier (HPA), a power glitch was observed with the characteristic of producing small 0.1-0.3 dB jumps in power across temperature. In order to troubleshoot this glitch behavior, a nonlinear model that could describe the saturation behavior of the HPA across temperature was desired. However, nonlinear device models were not available for the transistors and components within the HPA. Measured data of the HPA subassemblies were available but were of various formats, including s-parameters, nonlinear pin-pout curves, and fixed losses over temperature, and not easily modeled within commercial EDA (electronic design automation) simulation tools. This tool was built to be able to understand the gain/power distribution stackup and the sensitivities to power changes in the HPA over temperature.
Bi-manual Dexterous Manipulation for Maritime Explosive Ordnance DisposalTBMG-246455/1/2016
Since 2001, there has been a proliferation of robots within the U.S. military to assist with Explosive Ordnance Disposal (EOD) missions. Ground robotics systems are able to detect and dispose of Improvised Explosive Devices (IEDs) with the help of robotic manipulator arms.
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