Home/Connected Invariant Sets for High-Speed Motion Planning in Partially-Known Environments

Connected Invariant Sets for High-Speed Motion Planning in Partially-Known Environments

Daniel Althoff and Sebastian Scherer
Conference Paper, Carnegie Mellon University, 2015 IEEE International Conference on Robotics and Automation, March, 2015

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Ensuring safety in partially-known environments is a critical problem in robotics since the environment is perceived through sensors and the environment cannot be completely known ahead of time. Prior work has considered the problem of finding positive control invariant sets (PCIS). However, this approach limits the planning horizon of the motion planner since the PCIS must lie completely in the limited known part of the environment. Here we consider the problem of guaranteeing safety by ensuring the existence of at least one PCIS in partially-known environments leading to an extension of the PCIS concept. It is shown, that this novel method is less conservative than the common PCIS approach and robust to unknown small obstacles which might appear in the close vicinity of the robot. An example implementation for loiter circles and power line obstacles is presented. Simulation scenarios are used for validating the proposed concept.

BibTeX Reference
@conference{Althoff-2015-5924,
title = {Connected Invariant Sets for High-Speed Motion Planning in Partially-Known Environments},
author = {Daniel Althoff and Sebastian Scherer},
booktitle = {2015 IEEE International Conference on Robotics and Automation},
school = {Robotics Institute , Carnegie Mellon University},
month = {March},
year = {2015},
address = {Pittsburgh, PA},
}
2017-09-13T10:38:46+00:00