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

• Published in: 2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) pp. 261 - 262
• Main Authors: Zhao, Chenyu, Ruan, Ciyu, Wang, Shengbo, Zha, Jirong, Wang, Haoyang, Li, Jiaqi, Liu, Yuxuan, Wang, Xuzhe, Chen, Xinlei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 13.05.2024
• Subjects: Ground Effect; Image edge detection; Landing; Low-cost Sensing; Micro Aerial Vehicle; Organizations; Power demand; Propioception; Sensor systems; Signal processing; Visualization
• DOI: 10.1109/IPSN61024.2024.00031

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.