This paper presents a decentralized motion planner for a formation of autonomous mobile robots evolving in an unknown environment with obstacles. The motion planning scheme consists of decentralized receding horizon planners that reside on each vehicle to achieve coordination among formation agents. The advantage of the proposed algorithm is that each vehicle only requires local knowledge of its neighboring vehicles. The main requirement for designing an optimal conflict-free trajectory in a decentralized way, is that each robot does not deviate too far from its assumed trajectory designed without taking the coupling constraints into account. Finally, a comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages especially in terms of computing time.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in environments with obstacles. Instead of addressing motion planning and control in different contexts, these issues are described in connected modules with performance requirement considerations. The planning problem is formulated as a constrained receding horizon planning problem and is solved in real time with an efficient computational method that combines nonlinear control theory, B-spline basis function and nonlinear programming. An integral sliding mode controller is used for trajectory tracking. Closed-loop stability of the tracking errors is guaranteed in spite of unknown disturbances. It is also shown that this strategy is particularly useful if integral sliding mode control is combined with other methods to further robustify against perturbations. The effectiveness, perfect performance of obstacle avoidance, real time and high robustness properties are demonstrated by experimental results.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in an uncertain environment with obstacles. The proposed strategy consists in separating the path planning from the control algorithm. The path planning is done by computing the time optimal collisionfree trajectory which takes into account the limitations on the linear and angular speeds of the vehicle. The position and shape of obstacles are computed by a vision algorithm using a single camera. A saturated controller based on integral sliding mode is designed to solve the tracking problem in the presence of input saturations and of the unknown disturbances. The effectiveness, perfect performance of obstacle avoidance, real-time and high robustness properties are demonstrated by experimental results.

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