tinySLAM-based exploration with a swarm of nano-UAVs
Johan Markdahl, Mattias Vikgren

TL;DR
This paper presents a novel exploration method for nano-UAV swarms using tinySLAM and dynamic coverage algorithms, demonstrating effective mapping and exploration on hardware-limited platforms.
Contribution
It introduces a combined SLAM and exploration framework specifically designed for nano-UAV swarms with real-time implementation on limited hardware.
Findings
Successful mapping of environments using nano-UAVs
Stable exploration driven by modified dynamic coverage algorithm
Implementation on Crazyflie 2.1 platform demonstrates practicality
Abstract
This paper concerns SLAM and exploration for a swarm of nano-UAVs. The laser range finder-based tinySLAM algorithm is used to build maps of the environment. The maps are synchronized using an iterative closest point algorithm. The UAVs then explore the map by steering to points selected by a modified dynamic coverage algorithm, for which we prove a stability result. Both algorithms inform each other, allowing the UAVs to map out new areas of the environment and move into them for exploration. Experimental findings using the nano-UAV Crazyflie 2.1 platform are presented. A key challenge is to implement all algorithms on the hardware limited experimental platform.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotics and Sensor-Based Localization · Robotic Path Planning Algorithms · Distributed Control Multi-Agent Systems
