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.

The research works carried out in this paper deal with the control of a fast double-steering off-road mobile robot. Such kind of robots requires very high stable and accurate controllers because their mobility is particularly influenced by wheel-ground interactions. Hence, the vehicle dynamics should be incorporated in the control circuit to take into account these issues, which is developed based on the road geometry parameters and the slippage-friction conditions at the wheel-ground contacts. Relying on this dynamic model, we present in this paper the design and application of a constrained Model Predictive Control (MPC). It is based on the minimization of a cost function (optimizing the devi-

A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot-terrain interaction with the robot's quasi-static tip-over stability measure (assuming that the robot traverses uneven terrains at low speed for safety). The robot's stability is computed by first estimating the robot's pose, which in turn is interpreted as a contact problem, formulated as a linear complementarity problem (LCP), and solved using the Lemke's method (which guarantees a fast convergence). The present work compares the performance of the proposed algorithm to other RRT-like algorithms (in terms of planning time, rate of success in finding solutions and the associated cost values) over various uneven terrains and shows that the proposed algorithm can be advantageous over its counterparts in various aspects of the planning performance.

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This paper proposes a new wheel motion generator to track the centroidal motion of one quadrupedon-wheel robot which has the ability to cross various rough terrains with the model based wholebody torque control. The generator is used to track the whole-robot centroidal motion reference. Firstly, the wheel contact model and the whole-body inverse kinematics model are derived using spatial vectors. The wheel motion is extracted out mathematically depending on the base and the legged motions, which serves as the kinematics model. Then the wheel motion generator is developed by combining both the kinematics model and the robot centroidal momentum/dynamics model. The models are decomposed into three components relating to the base motion, the legged motion and the wheel motion. The adaptive wheel motion references are derived in a detailed mathematical way and several algorithms are developed for the model decompositions. Finally, the robot is simulated to be driven on various rough terrains using the operational space control framework mixed with our proposed compatible prioritized impedance controller. The required torque for multiple tasks is generated by the feed-forward and feedback controllers while fulfilling the contact constraints.