让六自由度机器人运动时始终看得见关键点，避免视觉遮挡
Continuous-Time Line-of-Sight Constrained Trajectory Planning for 6-Degree of Freedom Systems
- 基于连续时间建模，动态保持关键点在视野内
- 相比现有方法，视野丢失率更低，计算速度更快
- 适用于复杂非线性系统，适合无人机、机械臂等场景
感知算法在现代自主系统中广泛应用，依赖关键点的可见性以实现真实世界操作。许多算法要求关键点始终位于机器人的视线范围内才能可靠运行。本文解决机器人运动过程中维持关键点可视性的挑战。提出一种新方法，具备对不同传感器视场的适用性、对任意非线性系统动力学的适应性，以及路径全程持续的视线约束。实验表明，在多个典型且具有挑战性的场景中，该方法相比现有最优方法显著降低了视线丢失率并提升了运行效率。
原文摘要 · Abstract (English)
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.
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