Demo Abstract: Bio-inspired Tactile Sensing for MAV Landing with Extreme Low-cost Sensors.

Chenyu Zhao, Ciyu Ruan, Shengbo Wang, Jirong Zha, Haoyang Wang, Jiaqi Li,Yuxuan Liu, Xuzhe Wang,Xinlei Chen

International Symposium on Information Processing in Sensor Networks(2024)

引用 0|浏览0
暂无评分
摘要
MAV (Micro Aerial Vehicle) requires landing on a docking platform for recharging during or after missions due to their limited energy capacity. Inspired by biological tactile sensing, we propose a proprioceptive sensing system that allows MAV to "touch", recognize, and locate the landing platform even when visual or other positioning systems are not functioning properly. We leverage a physical phenomenon: as the MAV approaches a beneath obstacle, it experiences attitude disturbances caused by the airflow generated by the rotor’s reflections from the ground. By employing traditional signal processing and learning-based techniques to analyze signals from the IMU (Inertial Measurement Unit) and motors, the MAV can sense the edges of the platform and further calculate the precise landing coordinates. With a power consumption of less than 40 mW, our system achieves an edge detection error of less than 2 cm and a landing success rate exceeding 90%.CCS CONCEPTS• Applied computing → Aerospace; • Computing methodologies → Machine learning approaches; • Computer systems organization → Sensors and actuators.
更多
查看译文
关键词
Micro Aerial Vehicle,Ground Effect,Landing,Low-cost Sensing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要