Bio-inspired source seeking and obstacle avoidance on a palm-sized drone

Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones

“…Lightweight approaches better suited to nano-drones employ different sensors such as Time-of-Flight (ToF) ranging sensors [16], [17], [18]. These approaches can be implemented onboard and provide robust obstacle avoidance, even in unknown environments, with raw sensor readings or minimal onboard processing (e.g., 30 OP/s in [18]), such as simple buginspired lightweight state machines [16], [17]. However, in our competition, only a low-resolution monochrome monocular camera was allowed, narrowing the teams' effort only to visual-based approaches.…”