Title :
Path-finding in dynamic environments with PDDL-planners
Author :
Estivill-Castro, Vladimir ; Ferrer-Mestres, Jonathan
Author_Institution :
Sch. of ICT, Griffith Univ., Griffith, QLD, Australia
Abstract :
The standardization of planning problems by their descriptions in the PDDL has resulted in clear benchmarking of planners, and thus, in significant advances in reliable and efficient planning packages. The output of these classical planners is a plan as sequence of actions for the controllable robots in the environment. We show here that, provided that the adversaries follow a deterministic behavior, PDDL-planners can also be used in dynamic environments where uncontrollable adversaries may obstruct paths at some time in the future. Therefore, these environments can be used by mobile robots without the need to use more sophisticated planners where environments are modeled by Markov Decision Processes (MDPs). We created a planning API for integrating any PDDL-solver and use it to elaborate platform independent planning behavior. We also have the ability of switching between PDDL-solvers or to change the integration cycle of the planner. We show that these two features are essential for the dynamic environments considered here.
Keywords :
Markov processes; control engineering computing; mobile robots; path planning; MDP; Markov decision process; PDDL-planner; PDDL-solver; dynamic environment; integration cycle; mobile robot; path-finding; planning API; planning domain definition language; platform independent planning behavior; Communities; Heuristic algorithms; Navigation; Planning; Robot sensing systems; Unified modeling language; Adversarial Planning; Behaviour-based robotics; Navigation; Path and task planning; Robotic Architectures;
Conference_Titel :
Advanced Robotics (ICAR), 2013 16th International Conference on
Conference_Location :
Montevideo
DOI :
10.1109/ICAR.2013.6766456