Sequential Parametrized Motion Planning and its Complexity
Michael Farber, Amit Kumar Paul

TL;DR
This paper develops the theory of sequential parametrized motion planning, analyzing its complexity and introducing new concepts like TC-generating functions, with applications to multi-robot navigation and collision avoidance.
Contribution
It generalizes parametrized motion planning to sequential scenarios, analyzes the topological complexity of relevant fibrations, and introduces TC-generating functions for motion planning algorithms.
Findings
Analysis of the sequential parametrized topological complexity of the Fadell-Neuwirth fibration.
Introduction of TC-generating functions and exploration of their properties.
Application to multi-robot motion planning avoiding collisions.
Abstract
In this paper we develop theory of sequential parametrized motion planning which generalises the approach of parametrized motion planning, which was introduced recently in [3]. A sequential parametrized motion planning algorithm produced a motion of the system which is required to visit a prescribed sequence of states, in certain order, at specified moments of time. The sequential parametrized algorithms are universal as the external conditions are not fixed in advance but rather constitute part of the input of the algorithm. The second part of this article consists of a detailed analysis of the sequential parametrized topological complexity of the Fadell - Neuwirth fibration. In the language of robotics, sections of the Fadell - Neuwitrh fibration are algorithms for moving multiple robots avoiding collisions with other robots and with obstacles in Euclidean space. In the last section…
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Taxonomy
TopicsRobotic Path Planning Algorithms · History and Theory of Mathematics · Computability, Logic, AI Algorithms
