Actuator Networks: Inducing Potential Fields to Guide a Moving Element to a Desired Position Using Push-Cage-Squeeze Cycles∗

Building on recent work in sensor networks and distributed manipulation, we propose Actuator Networks– networks of devices capable of exerting influence on their environment in addition to monitoring it. We show how an Actuator Network can be used to guide a moving element to a desired location in space through the creation of potential gradients, and introduce an algorithm capable of calculating the required actuation. In this algorithm, motion is achieved with three steps: “Push, Cage, and Squeeze”, whose sequential application we term a PCS cycle. Guiding a moving element via PCS cycles is robust to modeled trajectory error and provides a framework into which path planning and obstacle avoidance can be integrated. We explore the PCS cycle as an example of one of the types of distributed actuation possible with an Actuator Network. We introduce models, notation, terms and properties related to the nature of Actuator Networks, describe the distributed guidance algorithm, and discuss simulation results showing how an Actuator Network with eight nodes can guide a moving element to a desired location while avoiding obstacles. ICRA keywords: Sensor Networks, Actuator Networks, Potential Fields, Motion Planning