ELLAS: Enhancing LiDAR Perception With Location-Aware Scanning Profile Adaptation
Thymon Rhemrev, Gideon Van Triest, J. Pronk, Ashish Pandharipande, Nitin Jonathan Myers
- 发表年份
- 2025
- 引用次数
- 4
摘要
Light detection and ranging (LiDAR) is used in robots and in automotives to obtain the perception of the surrounding environment. Traditional spinning LiDARs scan the environment uniformly along all angular directions by operating at a constant rotational speed, with fixed sensing parameters throughout a rotation. Such a sensing approach, however, is suboptimal when information about static obstacles in the environment is available at the LiDAR. In this work, we introduce ELLAS, a first-of-its-kind spinning LiDAR system that dynamically adapts its range and resolution over the field of view. This adaptation is achieved by optimizing the ranging parameters at the LiDAR and the instantaneous rotational speed of the spinning platform to the location of static objects in scene topology maps. With the optimized settings, ELLAS results in a longer range along directions where static obstacles are farther away and achieves a higher angular resolution around those directions.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002