⚡ 本页包含 AI 生成的分析内容，仅供参考
该论文提出了一种用于微机器人自主导航的路径规划处理器，采用IDA*算法实现2D/3D环境下的高效路径规划，每任务仅消耗1.5µJ能量，解决了微机器人电池续航有限的问题。
Autonomous micro robots have been deployed for various applications, ranging from unmanned package delivery to smart aerial surveillance. These robots possess intelligence for perception, make decisions based on the collected information, and take actions automatically [1], as illustrated in Fig. 21.2.1. Due to the limited battery lifetime of micro robots, energy-efficient processing for path planning is critical, especially in dynamic environments. In [2], a low-power path planning processor for 2D indoor navigation tasks through the iterative-deepening A* (IDA*) algorithm is proposed. IDA* is a grid-based planning algorithm, which finds a deterministic path on a pre-defined graph converted from a grid map. However, IDA* requires massive memory usage to store the entire map, leading to exponential complexity in memory storage and search time as the map size increases. For maps with an increased dimension and resolution, such as for
Chieh Chung, Chia-Hsiang Yang
National Taiwan University, Taipei, Taiwan