Ambroise Krebs

Performance comparison of rough-terrain robots—simulation and hardware

The design of a rover for a specific environment is a complex procedure which requires modeling a chassis and evaluating it with specific criteria. This is the aim of the performance optimization tool (POT) presented in this paper. The POT enables the comparison and optimization of a rover chassis in a quick and efficient way. The tool is based on a static approach including optimization of the wheel torques in order to maximize traction. Tests with real hardware were performed to validate the POT. Two different rovers, CRAB and RCL-E, were assessed in simulation and hardware with respect to specific, well defined metrics. In simulation, their performances were compared to the rocker-bogie-type rover MER. CRAB and MER showed similar performance, while RCL-E had significant problems with the benchmark obstacle. A very good match between simulation results and real measurements was achieved.

Rover control based on an optimal torque distribution - Application to 6 motorized wheels passive rover

The capability to overcome terrain irregularities or obstacles, named terrainability, is mostly dependant on the suspension mechanism of the rover and its control. For a given wheeled robot, the terrainability can be improved by using a sophisticated control, and is somewhat related to minimizing wheel slip. The proposed control method, named torque control, improves the rover terrainability by taking into account the whole mechanical structure. The rover model is based on the Newton-Euler equations and knowing the complete state of the mechanical structures allows us to compute the force distribution in the structure, and especially between the wheels and the ground. Thus, a set of torques maximizing the traction can be used to drive the rover. The torque control algorithm is presented in this paper, as well as tests showing its impact and improvement in terms of terrainability. Using the CRAB rover platform, we show that the torque control not only increases the climbing performance but also limits odometric errors and reduces the overall power consumption.

Performance Optimization of All-Terrain Robots: A 2D Quasi-Static Tool

The creation of a rover for a specific task requires designing and selecting the mechanical structure specifically for its mission. This can be done by modelling a chassis and evaluating it with specific criteria, which is the aim of the performance optimization tool presented here. This software makes it possible to compare and improve existing and new designs in a quick and efficient way. The tool presented in this paper is based on a quasi-static approach including optimization of the friction coefficients to model and evaluate the rover

Comparison of Boosting based Terrain Classification using Proprioceptive and Exteroceptive Data

The terrain classification is a very important subject to the all-terrain robotics community. The knowledge of the type of terrain allows a rover to deal with its environment more efficiently. The work presented in this paper shows that it is possible to differentiate terrains based on their aspects, using exteroceptive sensors, as well as based on their influence on the rover’s behavior, using proprioceptive sensors. Using a boosting method (AdaBoost), these two sets of classifiers are trained and applied independently. The resulting dual algorithm identifies offline the nature of the terrain on which the vehicle is virtually driving and classifies it according to categories previously labeled, such as sand or grass. Due to the good results obtained for the classification based solely on each type of sensor, this paper concludes that the correlation between data from proprioceptive and exteroceptive sensors could be used for further applications. This paper is a summarized version of the one presented at the ISER conference.

Antarctica Rover design and optimization for limited power consumption

Abstract The design process of the new locomotion platform called K11 aims at obtaining a rover capable of traveling thousands of kilometers at 1 m/s in the harsh environment of Antarctica during summer and carrying a 100 kg payload. A model including the drive-train power consumption and masses is used to optimize the parameters of the rover in order to minimize the power consumption. The obtained configuration consumes theoretically only 58W on flat ground and has limited power consumption while climbing a slope. The prototype built based on the optimization results is used to confirm the model.

Composite control based on optimal torque control and adaptive Kriging control for the CRAB rover

Terrainability is mostly dependant on the suspension mechanism and the control of a space rover. For the six wheeled CRAB rover, this paper presents the composite control design with torque control and adaptive Kriging control to improve the terrainability, somewhat related to minimizing wheel slip. As CRAB is moving slowly, the torque control is processed by minimizing the variance of the required friction coefficient based on the static model. Adaptive Kriging control is used to track the commanded velocity. The system uncertainty is compensated by Kriging estimation based on the velocity dynamics. Experiment results with two different tires show the effectiveness of the control scheme.