Pascal Lépinay

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This paper proposes an algorithm that drives a unicycle type robot to a desired path, including obstacle avoidance capabilities. The path following control design relies on Lyapunov theory, backstepping techniques and deals explicitly with vehicle dynamics. Furthermore, it overcomes initial condition constraint present in a number of path following control(More)
This paper proposes an algorithm that drives a unicycle type robot to a desired path, including obstacle avoidance capabilities. The path-following control design relies on Lyapunov theory, backstep-ping techniques and deals explicitly with vehicle dynamics. Furthermore , it overcomes the initial condition constraints present in a number of path-following(More)
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In order to achieve the autonomy of mobile robots, effective localization is a necessary prerequisite. In this paper, we propose an improved Monte Carlo localization using self-adaptive samples, abbreviated as SAMCL. This algorithm employs a pre-caching technique to reduce the on-line computational burden. Further, we define the concept of similar energy(More)
In order to achieve the autonomy of mobile robots, effective localization is a necessary prerequisite. In this paper, we propose an improved Monte Carlo localization using self-adaptive samples, abbreviated as SAMCL. This algorithm is able to solve the multi-robot localization problem as well as the single-robot localization problem. By employing a(More)
This paper describes the realization of a biologically-based vision system for autonomous mobile robots. This system presents two main aspects: a multi-modal vision (fovea and peripheral vision) coupled with a collision avoidance algorithm. We have carried out all the simulations of this system and realized several prototyping boards. The prototyping on(More)