2009/12/01 by Nicolas A. Barriga, Barriga, Nicolas A.
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Control and Dynamics of Mobile Robots #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization #cs.AI #cs.RO
paper · pdf · doi:10.48550/arxiv.0912.0270
54 pages, Master of Science in Informatics Engineering thesis
arxiv created 2009/12/01 · openalex publication_date 2009/12/01 · arxiv updated 2009/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This document is a thesis on the subject of single-agent on-line path planning in continuous,unpredictable and highly dynamic environments. The problem is finding and traversing a collision-free path for a holonomic robot, without kinodynamic restrictions, moving in an environment with several unpredictably moving obstacles or adversaries. The availability of perfect information of the environment at all times is assumed. Several static and dynamic variants of the Rapidly Exploring Random Trees (RRT) algorithm are explored, as well as an evolutionary algorithm for planning in dynamic environments called the Evolutionary Planner/Navigator. A combination of both kinds of algorithms is proposed to overcome shortcomings in both, and then a combination of a RRT variant for initial planning and informed local search for navigation, plus a simple greedy heuristic for optimization. We show that this combination of simple techniques provides better responses to highly dynamic environments than the RRT extensions.