Human-guided Swarms: Impedance Control-inspired Influence in Virtual Reality Environments

As the potential for societal integration of multi-agent robotic systems increases [1], the need to manage the collective behaviors of such systems also increases [2, 3, 4]. There has been significant research effort directed towards the examination of how humans can assist in controlling such collective behaviors, such as in human-swarm interactions [5, 6, 7]. Agent-agent interactions in a swarm of small unmanned aerial systems (sUAS) lead to the emergence of collective behaviors that enable effective coverage and exploration across large spatial extents. However, the same inherent collective behaviors can occasionally limit the ability of the sUAS swarm to focus on specific objects of interest during coverage or exploration missions [8]. In these scenarios, the human operator or supervisor should have the opportunity to fractionally revoke or limit emergent swarm behaviors, and guide the swarm to achieve mission objectives. For most applications, including in industry-and defense-related contexts, such human-swarm interaction (HSI) will likely require intuitive and predictable mechanisms of control to quickly translate the input of the human (such as a gesture) to an influence or effect on the sUAS swarm. The goal of our work is to create an intuitive interface for a human supervisor to influence or guide an sUAS swarm without excessive incursions on decentralized control afforded by these systems, while attempting to create more predictable behaviors. This is a potentially valuable approach that can enable the fully utilization of swarm capabilities, while also retaining an ongoing macroscopic-level of swarm control in scenarios where focus on specific regions of interest is required (e.g., search and rescue, surveillance operations) [9]. The influence mechanism has been implemented and tested using 16 drones in a photo-realistic virtual reality (VR) environment (as shown in Figure 1).