Petras Swissler

Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu et al.

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.

Lindsay Burke, Maxfield Comstock, Jason Graham et al.

Demand-responsive transit (DRT) is a flexible alternative to traditional, fixed-route mass-transit networks. Although DRT can function well in low-density communities, high operating costs and low reliability are common issues. We propose that these issues can be mitigated by moving from a centralized, manually-scheduled scheme to a distributed system capable of dynamically routing multiple vehicles using a slime-mold-inspired routing algorithm to maximize network effectiveness. We additionally introduce the method of dynamic transfers to further optimize transit network efficiency. All passenger allocation and dynamic transfers are handled via a continual cooperative bidding process by the buses. In this paper, we present simulated results for a swarm-driven transit network in suburban, urban, and semi-rural scenarios, using map networks pulled from OpenStreetMap. We show that our approach increases passenger delivery rates relative to a fixed-network approach by 28%, 49%, and 101%, respectively, and results in over 75% reduction in walking time in all cases.