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We propose a novel Human-Swarm Interaction (HSI) framework which enables theuser to control a swarm shape and formation. The user commands the swarmutilizing just arm gestures and motions which are recorded by an off-the-shelfwearable armband. We propose a novel interpreter system, which acts as anintermediary between the user and the swarm to simplify the user's role in theinteraction. The interpreter takes in a high level input drawn using gesturesby the user, and translates it into low level swarm control commands. Thisinterpreter employs machine learning, Kalman filtering and optimal controltechniques to translate the user input into swarm control parameters. A notionof Human Interpretable dynamics is introduced, which is used by the interpreterfor planning as well as to provide feedback to the user. The dynamics of theswarm are controlled using a novel decentralized formation controller based ondistributed linear iterations and dynamic average consensus. The framework isdemonstrated theoretically as well as experimentally in a 2D environment, witha human controlling a swarm of simulated robots in real time.

Gesture based Human-Swarm Interactions for Formation Control using interpreters