Scaling the Dynamic Approach to Autonomous Path Planning: Planning Horizon Dynamics
Abstract
In the dynamical systems approach to robot path planning both sensed and remembered information contribute to shape a nonlinear vector field that governs the behavior of an autonomous agent. Such systems perform well with partial knowledge of the environment and in dynamically changing environments. Nevertheless, it is a local heuristic approach to path planning, and it is not guaranteed to find existing paths. We describe a method of adjusting the spatial resolution of the planner using a dynamical system that operates at a faster time scale than the planning dynamics. This improves the system's ability to utilize both sensed and remembered information, and to solve a larger range of problems without resorting to global path planning. 1
Cite
Text
Large et al. "Scaling the Dynamic Approach to Autonomous Path Planning: Planning Horizon Dynamics." International Joint Conference on Artificial Intelligence, 1997.Markdown
[Large et al. "Scaling the Dynamic Approach to Autonomous Path Planning: Planning Horizon Dynamics." International Joint Conference on Artificial Intelligence, 1997.](https://mlanthology.org/ijcai/1997/large1997ijcai-scaling/)BibTeX
@inproceedings{large1997ijcai-scaling,
title = {{Scaling the Dynamic Approach to Autonomous Path Planning: Planning Horizon Dynamics}},
author = {Large, Edward W. and Christensen, Henrik I. and Bajcsy, Ruzena},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1997},
pages = {1360-1365},
url = {https://mlanthology.org/ijcai/1997/large1997ijcai-scaling/}
}