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.read more
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Journal ArticleDOI
Randomised kinodynamic motion planning for an autonomous vehicle in semi-structured agricultural areas
Mohamed Elbanhawi,Milan Simic +1 more
TL;DR: In this article, a randomised motion planner is presented that operates within a suitable timeframe for constrained mobile robots in agricultural environment, which relies on splitting planning into two efficient phases to reduce its computational time.
Journal ArticleDOI
A robust fuzzy logic path tracker for non-holonomic mobile robots
TL;DR: In this paper the path tracking problem for non-holonomic mobile robots is dealt with and a robust fuzzy logic controller that steers the car to the appropriate direction is proposed.
Journal ArticleDOI
Admissible velocity propagation: Beyond quasi-static path planning for high-dimensional robots:
TL;DR: This work proposes a method that enables path-velocity decomposition to discover truly dynamic motions, i.e. motions that are not quasi-statically executable, and demonstrates the efficiency of the proposed method on some difficult kinodynamic planning problems, where, in particular, quasi-static methods are guaranteed to fail.
Journal ArticleDOI
A gradient-based path optimization method for motion planning
TL;DR: A basic gradient-based algorithm is proposed that transforms a polygonal collision-free path into a shorter one, requiring only collision checking, and not any time-consuming obstacle distance computation nor geometry simplification.
Journal ArticleDOI
A Multiple Models Approach for Adaptation and Learning in Mobile Robots Control
TL;DR: The experimental results are satisfactory in terms of tracking errors and computational efforts and show the improvement in the tracking performance when the proposed methodology is used for tracking tasks in dynamical uncertain environments.