Abstract In this paper we introduce the k-Dynamic Dubins TSP with Neighborhoods (k-DDTSPN), the problem consisting of planning efficient paths among a set of target regions dynamically selected in the environment for multiple robots with bounded curvature (Dubins vehicle). We propose a decentralized auction-based technique, which uses a greedy constructive strategy to dynamically calculate the cost of insertion of the new region to each path and selects the one with the minimum impact on the length. We provide a formal analysis of the proposed technique, presenting an upper bound for the length of the longest tour. Several trials were executed in a simulated environment, allowing for a statistical investigation of the results.
Adaptive Path Planning for Multiple Vehicles with Bounded Curvature
2015-01-01
16 pages
Article/Chapter (Book)
Electronic Resource
English
Continuous-curvature path planning for car-like vehicles
Tema Archive | 1997
|On the Path Curvature of Vehicles
British Library Conference Proceedings | 1995
|Adaptive Path Tracking Controller for Intelligent Driving Vehicles for Large Curvature Paths
SAE Technical Papers | 2022
|Curvature-Optimal Path Planning and Servoing for Autonomous Vehicles: A Neural Net Implementation
British Library Conference Proceedings | 1993
|