Actively articulated locomotion systems such as hybrid wheel-legged vehicles are a possible way to enhance the locomotion performance of an autonomous mobile robot. In this paper, we address the control of the wheel-legged robot Hylos traveling on irregular sloping terrain. The redundancy of such a system is used to optimize both the balance of traction forces and the tipover stability. The general formulation of this optimization problem is presented, and a suboptimal but computationally efficient solution is proposed. Then, an algorithm to control the robot posture, based on a velocity model, is described. Finally, this algorithm is validated through simulations and experiments that show the capabilities of such a redundantly actuated vehicle to enhance its own safety and autonomy in critical environments.

To cite this version:Christophe Grand, Faïz Ben Amar, Frédéric Plumet. Motion kinematics analysis of wheeled-legged rover over 3D surface with posture adaptation. Mechanism and Machine Theory, Elsevier, 2010, 45 (3), pp.477-495. 10.1016/j.mechmachtheory.2009 Motion kinematics analysis of wheeled-legged rover over 3D surface with posture adaptation AbstractThis paper proposes a general formulation of the kinetostatic model of articulated wheeled rovers that move on rough terrains. Differential kinematic model is used to control the generalized trajectory of the robot, composed of position and posture parameters. These posture parameters have been optimized in order to provide high stability and traction performance, during motion on irregular ground surface. Numerical simulation and experimental results, carried out on a hybrid wheeledlegged robot, show the validity of the approach presented in this paper.

This paper addresses the control of a hybrid wheellegged system evolving on rough terrain. First, the posture and trajectory parameters are introduced. Then, a decoupled posture and trajectory control algorithm based on the velocity model of the robot is proposed. Last, the performance and feasibility of the control algorithm are evaluated through simulations and experiments with the Hylos robot.