Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
For swarm and field robotics researchers, this work provides a low-cost, rapid-deployment platform for real-world validation, though the approach is incremental as it offloads hardware challenges to humans.
The paper introduces the Bionic Swarm, a human-in-the-loop system that lowers barriers to real-world swarm robotics validation by having humans execute robot actions via a smartphone app. The Score-Biased-Search algorithm achieves superlinear map reconstruction relative to the number of agents, and the system was validated in outdoor soil mapping.
Swarm and field robotics face significant barriers to real-world validation due to the high cost and development time to deploy hardware. This paper introduces the ``Bionic Swarm,'' a novel system that lowers these barriers by abstracting away many of the tasks that are difficult to implement on robots but which do not contribute to the overall algorithm evaluation, giving these tasks to human users. These human users take directions from a smartphone web-app that takes measurements from Bluetooth-connected sensors and relays them to a centralized server. This server runs the swarm algorithm and directs actions to the human users. We evaluate this system through the experimental validation of a geotechnically-focused search algorithm named Score-Biased-Search, which functions by assigning a ``score'' to each location on a reconstructed map, then biases search patterns through areas of higher expected scores, and which exhibits superlinear map reconstruction relative to the number of search agents. After presenting simulation results for the algorithm, we then apply the algorithm on the Bionic Swarm platform to validate its function in a real-world, outdoor setting. This work demonstrates that this human-in-the-loop approach significantly lowers the barrier to entry for field and swarm robotics research.