This paper deals with the optimization of Robot-Obstacle interaction computations, in the context of non-holonomic trajectory deformation for mobile robots. We first recall the principle of the trajectory deformation and the role of the potential field gradient in the configuration space. The contribution of the paper is twofold. First we show that the potential field gradient can be computed without any closed-form expression of the potential function if this latter depends only on the distance between the robot and the obstacles. Then an algorithm to filter obstacles that have no influence in Robot-Obstacle interactions is presented. This algorithm takes advantage of the spatial coherence of the planned trajectory, and has been evaluated by experiments on mobile robot Hilare2 towing a trailer.

This paper presents a novel and generic approach of path optimization for nonholonomic systems. The approach is applied to the problem of reactive navigation for nonholonomic mobile robots in highly cluttered environments. This is a collision-free initial path being given for a robot, and obstacles detected while following this path can make it in collision. The current path is iteratively deformed in order to get away from obstacles and satisfy the nonholonomic constraints. The core idea of the approach is to perturb the input functions of the system along the current path in order to modify this path, making an optimization criterion decrease.

In this paper, we present a method to follow a planned trajectory in a highly cluttered environment for complex nonholonomic systems. This method ensures, under some hypotheses, that the robot never collides. When a collision is detected on the trajectory, we compute a deceleration interval to stop the robot while decelerating, we deform the trajectory in such a way that the trajectory is always feasible.

In this paper, we propose a novel approach to reactive obstacle avoidance for nonholonomic systems. The method is based on the deformation of an initial trajectory computed by a motion planner. The deformation we perform keeps the nonholonomic constraints of the system satisfied. The deformation algorithm is based on a potential field generated by obstacles. We applied this approach to the mobile robot Hilare 2 towing a trailer and we carried out some experiments.

This article presents an algorithm that determines safe motions for an articulated rover on rough terrains. It relies on the evaluation of a set of elementary trajectories on a digital elevation map built as the rover moves. The algorithm relies on the explicit computation of geometric constraints on the rover chassis. It has been integrated within a continuously running navigation loop on board the robot Lama, and tested under various terrain conditions.