50 research outputs found

    Slope Traversal Experiments with Slip Compensation Control for Lunar/Planetary Exploration Rover

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    2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, May 19-23, 200

    Slope traversal experiments with slip compensation control for lunar/planetary exploration rover

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    Abstract-This paper presents slope traversal experiments with slip compensation control for lunar/planetary exploration rovers. On loose soil, wheels of the rover easily slip even when the rover travels with relatively low velocity. Because of the slip, following an arbitrary path on loose soil becomes a difficult task for the rover, and also, the slip will increase when the rover traverses a slope. To cope with the slip issue, the authors previously proposed path following control strategy taking wheel slippages into account. Through numerical simulations in the previous work, it has been confirmed that the proposed control effectively compensates and reduces the slip motions of the rover, and then, the rover can follow a given path. In order to confirm the usefulness of the proposed control for practical application, slope traversal experiments using a fourwheeled rover test bed are addressed in this paper. The control performance of the slip compensation is compared to that of no slip control based on motion traces of the rover in side slope traversal case. Further, the effectiveness of the proposed control is verified by quantitative evaluations of distance and orientation errors

    Fault-Tolerant Control Strategy for Steering Failures in Wheeled Planetary Rovers

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    Fault-tolerant control design of wheeled planetary rovers is described. This paper covers all steps of the design process, from modeling/simulation to experimentation. A simplified contact model is used with a multibody simulation model and tuned to fit the experimental data. The nominal mode controller is designed to be stable and has its parameters optimized to improve tracking performance and cope with physical boundaries and actuator saturations. This controller was implemented in the real rover and validated experimentally. An impact analysis defines the repertory of faults to be handled. Failures in steering joints are chosen as fault modes; they combined six fault modes and a total of 63 possible configurations of these faults. The fault-tolerant controller is designed as a two-step procedure to provide alternative steering and reuse the nominal controller in a way that resembles a crab-like driving mode. Three fault modes are injected (one, two, and three failed steering joints) in the real rover to evaluate the response of the nonreconfigured and reconfigured control systems in face of these faults. The experimental results justify our proposed fault-tolerant controller very satisfactorily. Additional concluding comments and an outlook summarize the lessons learned during the whole design process and foresee the next steps of the research

    Learned and Controlled Autonomous Robotic Exploration in an Extreme, Unknown Environment

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    Exploring and traversing extreme terrain with surface robots is difficult, but highly desirable for many applications, including exploration of planetary surfaces, search and rescue, among others. For these applications, to ensure the robot can predictably locomote, the interaction between the terrain and vehicle, terramechanics, must be incorporated into the model of the robot's locomotion. Modeling terramechanic effects is difficult and may be impossible in situations where the terrain is not known a priori. For these reasons, learning a terramechanics model online is desirable to increase the predictability of the robot's motion. A problem with previous implementations of learning algorithms is that the terramechanics model and corresponding generated control policies are not easily interpretable or extensible. If the models were of interpretable form, designers could use the learned models to inform vehicle and/or control design changes to refine the robot architecture for future applications. This paper explores a new method for learning a terramechanics model and a control policy using a model-based genetic algorithm. The proposed method yields an interpretable model, which can be analyzed using preexisting analysis methods. The paper provides simulation results that show for a practical application, the genetic algorithm performance is approximately equal to the performance of a state-of-the-art neural network approach, which does not provide an easily interpretable model.Comment: Published in: 2019 IEEE Aerospace Conference Date of Conference: 2-9 March 2019 Date Added to IEEE Xplore: 20 June 201

    Simulation and Control of a Passively Articulated, Segmented-Body Rover

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    Mobility will be a key aspect of future planetary surface missions. A rover with several segments connected by rotary joints promises much capability in terrain traversal, but is not well understood. In this thesis, a computer model was built to simulate the movements of a passively articulated, segmented-body rover. Its main components are a linearized soil-wheel interaction model, a Newton-Euler based dynamic model, and a PD control module to regulate steering and handle disturbances. The simulation outputs were compared against results from past research on fixed-chassis vehicles. Next, the simulation was used to investigate the driving and turning behavior of articulated vehicles, and their controllability using a simple control system. It was found that the vehicle is relatively stable, and that simple control is possible

    Path-Following Control of Wheeled Planetary Exploration Robots Moving on Deformable Rough Terrain

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    The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip
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