BookDOI
Robot Motion Planning and Control
Jean-Paul Laumond
- Iss: 229
TLDR
Guidelines in nonholonomic motion planning for mobile robots and collision detection algorithms for motion planning are presented.Abstract:
Guidelines in nonholonomic motion planning for mobile robots.- Geometry of nonholonomic systems.- Optimal trajectories for nonholonomic mobile robots.- Feedback control of a nonholonomic car-like robot.- Probabilistic path planning.- Collision detection algorithms for motion planning.read more
Citations
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Journal ArticleDOI
An Optimality Principle Governing Human Walking
TL;DR: This paper investigates different possible strategies underlying the formation of human locomotor trajectories in goal-directed walking and finds that the variation (time derivative) of the curvature of the locomotor paths is minimized.
Journal ArticleDOI
Direct Trajectory Optimization Using a Variable Low-Order Adaptive Pseudospectral Method
TL;DR: In this paper, a variable-order adaptive pseudospectral method is presented for solving optimal control problems, which adjusts both themesh spacing and the degree of the polynomial on each mesh interval until a specified error tolerance is satisfied.
Journal ArticleDOI
Asymptotically optimal sampling-based kinodynamic planning
TL;DR: Two new methods, STABLE_SPARSE_RRT (SST) and SST*, result from this analysis, which are asymptotically near-optimal and optimal, respectively, and are shown to converge fast to high-quality paths, while they maintain only a sparse set of samples, which makes them computationally efficient.
Book ChapterDOI
Control of Wheeled Mobile Robots: An Experimental Overview
TL;DR: In this article, the motion control problem of wheeled mobile robots (WMRs) is addressed with reference to the unicycle kinematics and several control strategies for trajectory tracking and posture stabilization in an environment free of obstacles.
Journal ArticleDOI
Cooperative Path Planning for Target Tracking in Urban Environments Using Unmanned Air and Ground Vehicles
TL;DR: A cooperative path planning algorithm for tracking a moving target in urban environments using both unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs) and taking into account vision occlusions due to obstacles in the environment is described.