Guiding vector fields for robot motion control
Language: English Series: Springer tracts in advanced robotics | / edited by Bruno Siciliano and Oussama Khatib ; ; v.154Publication details: Springer 2023 SwitzerlandDescription: xxx, 255pISBN:- 9783031291517
- 629.892 Y18g
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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PK Kelkar Library, IIT Kanpur | General Stacks | 629.892 Y18g (Browse shelf(Opens below)) | Available | A186493 |
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629.892 X47s Smart maintenance for human-robot interaction | 629.892 Y15a Advanced technologies in modern robotic applications | 629.892 Y161m Modular Robots | 629.892 Y18g Guiding vector fields for robot motion control | 629.892 Y9h Human-robot interaction control using reinforcement learning | 629.892 Y9m Motion control of biomimetic swimming robots | 629.892 Z37w WHAT EVERY ENGINEER SHOULD KNOW ABOUT ROBOTS |
Using a designed vector field to guide robots to follow a given geometric desired path has found a range of practical applications, such as underwater pipeline inspection, warehouse navigation, and highway traffic monitoring. It is thus in great need to build a rigorous theory to guide practical implementations with formal guarantees. It is even so when multiple robots are required to follow predefined desired paths or maneuver on surfaces and coordinate their motions to efficiently accomplish repetitive and laborious tasks.
The book introduces guiding vector fields on Euclidean spaces and Riemannian manifolds for single-robot and multi-robot path-following and motion coordination, provides rigorous theoretical guarantees of vector field guided motion control of robotic systems, and elaborates on the practical implementation of the proposed algorithms on mobile wheeled robots and fixed-wing aircraft. It provides guidelines for the robust, reliable, and safe practical implementations for robotic tasks, including path-following navigation, obstacle-avoidance, and multi-robot motion coordination.
In particular, the book reveals fundamental theoretic underpinnings of guiding vector fields and applies to addressing various robot motion control problems. Notably, it answers many crucial and challenging questions such as:
· How to generate a general guiding vector field on any n-dimensional Riemannian manifold for robot motion control tasks?
· Do singular points always exist in a general guiding vector field?
· How to generate a guiding vector field that is free of singular points?
· How to design control algorithms based on guiding vector fields for different robot motion control tasks including path-following, obstacle-avoidance, and multi-robot distributed motion coordination?
Answering these questions has led to the discovery of fundamental assumptions, a “topological surgery” to create a singularity-free guiding vector field, a robot navigation algorithm with the global convergence property, a provably safe collision-avoidance algorithm and an effective distributed motion control algorithm, etc
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