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BookDOI

Robot Motion Planning and Control

Jean-Paul Laumond
- Iss: 229
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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.

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Dissertation

Contributions à la planification de mouvement

TL;DR: HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not, for teaching and research institutions in France or abroad, or from public or private research centers.
Proceedings ArticleDOI

A Novel Assistive Controller Based on Differential Geometry for Users of the Differential-Drive Wheeled Mobile Robots

TL;DR: In this article , a novel assistive control strategy based on differential geometry relying on only joystick inputs and vehicle states where the controller does not require any desired states is presented, and the geometric controller using the Darboux frame kinematics is designed for smooth trajectories under certain safety constraints.
Proceedings ArticleDOI

Path Planning of Tractor-trailer Mobile Robot in Multi-grid Circuit Map

TL;DR: A path planner for tractor-trailer robots based on multi-grid circuit map is proposed and designed according to the phenomenon that more current flows along the branch with fewer resistor in series and more resistors in parallel, which is similar with the aim of path planning for short and wide path.
Proceedings ArticleDOI

The design of arm linkages with decoupled dynamics taking into account the changing payload

TL;DR: The proposed approach improves the known design concepts permitting the dynamic decoupling of serial manipulators taking into account the changing payload, and is a symbiosis of mechanical and control solutions.
Book ChapterDOI

Bio-inspired control model for object manipulation by humanoid robots

TL;DR: A bio-inspired control model for humanoid robots manipulating objects is presented and an artificial neural network (RBF) is used to extract some features of the dynamic model automatically complementing the control scheme.