Multi-sensory Anti-collision Design for Autonomous Nano-swarm Exploration
2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS)(2023)
摘要
This work presents a multi-sensory anti-collision system design to achieve
robust autonomous exploration capabilities for a swarm of 10 cm-side
nano-drones operating on object detection missions. We combine lightweight
single-beam laser ranging to avoid proximity collisions with a long-range
vision-based obstacle avoidance deep learning model (i.e., PULP-Dronet) and an
ultra-wide-band (UWB) based ranging module to prevent intra-swarm collisions.
An in-field study shows that our multisensory approach can prevent collisions
with static obstacles, improving the mission success rate from 20% to 80% in
cluttered environments w.r.t. a State-of-the-Art (SoA) baseline. At the same
time, the UWB-based sub-system shows a 92.8% success rate in preventing
collisions between drones of a four-agent fleet within a safety distance of 65
cm. On a SoA robotic platform extended by a GAP8 multi-core processor, the
PULP-Dronet runs interleaved with an objected detection task, which constraints
its execution at 1.6 frame/s. This throughput is sufficient for avoiding
obstacles with a probability of about 40% but shows a need for more capable
processors for the next-generation nano-drone swarms.
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关键词
Autonomous exploration,Nano-drone Swarm,multi-sensory collision-avoidance
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