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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Automated guided vehicles (agv): searching a path in the flexible manufacturing systems pojazdy kierowane automatycznie (agv): poszukiwanie drogi w elastycznych systemach wytwarzania
TL;DR: In this article, a study of the trajectories and a simulation model of a hypothetical system, which included a FMS environment, were developed, and a potential field's method was explored in order to improve the ability of detecting obstacles in AGVs with trailers moving through stations.
Three-dimensional reachable set at instant for the dubins car: Properties of extremal motions
TL;DR: In this paper, the authors highlight the cases when the Pontryagin maximum principle (PMP) is both necessary and sufficient condition for the motions leading onto the boundary of the reachable set at a given instant.
Proceedings ArticleDOI
A Global-Local Approach for Trajectory Generation on Rough Terrain
TL;DR: Specially derived weight functions are used to construct a globally continuous function that provides a way of using local information to construct near-optimal trajectories, which is useful in the context of numerically solving nonlinear trajectory generation problems.
Proceedings ArticleDOI
Posture stabilization using a model free controller
TL;DR: Simulation results show the applicability of the control method for the posture stabilization of the car-like robot with no a-priori knowledge about the model of the robot.
Robust SLAM and Path Planning under Uncertainty for Autonomous Driving
TL;DR: SROM’s ability to maintain localization at low sampling rates or at high linear or angular velocities where most popular LiDAR-based localization approaches get degraded fast is showcased and the results demonstrate better accuracy in comparisons to other state-of-the-art methods with reduced computational expense aiding in real-time realizations.