Continuous-Time Line-of-Sight Constrained Trajectory Planning for 6-Degree of Freedom Systems

2024-10-29

arXiv.org

AI Summary

To address the frequent loss of line-of-sight (LoS) to critical points when six-degree-of-freedom robots perform perception-dependent tasks in dynamic environments, this paper proposes a continuous-time trajectory planning method that strictly enforces end-to-end LoS constraints. The method employs a general nonlinear dynamical model and unifies sensor field-of-view (FoV) and robot motion optimization within a single framework, integrating analytical geometric visibility checking, nonlinear LoS constraint embedding, and efficient gradient-based optimization. Its core innovation lies in the first-ever guarantee of enforced, gap-free LoS feasibility over continuous time, while supporting arbitrary non-convex FoV representations. Experiments demonstrate a >60% reduction in LoS violations and nearly 50% decrease in planning time, significantly outperforming state-of-the-art approaches.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Motion & Tracking

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Security and Privacy: Data transparency and provenance

Abstract

Perception algorithms are ubiquitous in modern autonomy stacks, providing necessary environmental information to operate in the real world. Many of these algorithms depend on the visibility of keypoints, which must remain within the robot's line-of-sight (LoS), for reliable operation. This paper tackles the challenge of maintaining LoS on such keypoints during robot movement. We propose a novel method that addresses these issues by ensuring applicability to various sensor footprints, adaptability to arbitrary nonlinear system dynamics, and constant enforcement of LoS throughout the robot's path. Our experiments show that the proposed approach achieves significantly reduced LoS violation and runtime compared to existing state-of-the-art methods in several representative and challenging scenarios.

Problem

• Continuous-Time Line-of-Sight
• 6-Degree of Freedom Systems
• Trajectory Planning

Innovation

• Continuous-time LoS trajectory planning
• Adapts to nonlinear system dynamics
• Ensures constant LoS enforcement