Aerial Transportation of Cable-Suspended Loads with an Event Camera

• Published in: IEEE robotics and automation letters Vol. 9; no. 1; pp. 1 - 8
• Main Authors: Panetsos, Fotis, Karras, George C., Kyriakopoulos, Kostas J.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerial Systems: Applications; Aerial Systems: Perception and Autonomy; Algorithms; Angular velocity; Autonomous aerial vehicles; Cameras; Curves; Estimation; Event Camera; Feedback; Indoor environments; Mathematical models; Motion capture; Multirotor; Nonlinear control; Predictive control; Robot vision systems; Slung-load Transportation; Suspended load; Transportation; Unmanned aerial vehicles; Voltage control
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2023.3333245

In this work, we investigate the integration of a Dynamic Vision Sensor (DVS) into an Unmanned Aerial Vehicle (UAV) with a cable-suspended load in order to achieve a robust and fast estimation of the cable's state during the transportation of the load. Based on the advantageous properties of event cameras, our ultimate goal is to design a computationally lightweight event processing method that persistently identifies the cable and estimates its complete state - required for any controller with feedback of the cable's state - within a much shorter time period compared to frame-based algorithms. Using a point cloud representation for the incoming event streams, the proposed method achieves the fast detection of the cable while the respective measurements are afterward fitted to a Bézier curve in order to approximate both the cable angle and angular velocity. Our method is initially validated in an indoor environment, where ground truth is available from a motion capture system, and is subsequently deployed in an outdoor one in order to evaluate its robustness against noise. Throughout the outdoor experiment, the feedback provided by the DVS is incorporated into a Nonlinear Model Predictive Control (NMPC) scheme which drives an octorotor towards reference setpoint positions while minimizing the cable angular motion.