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In this report for the Nasa NIAC Phase I study, we present a mission architecture and a robotic platform, the Shapeshifter, that allow multi-domain and redundant mobility on Saturns moon Titan, and potentially other bodies with atmospheres. The Shapeshifter is a collection of simple and affordable robotic units, called Cobots, comparable to personal palm-size quadcopters. By attaching and detaching with each other, multiple Cobots can shape-shift into novel structures, capable of (a) rolling on the surface, to increase the traverse range, (b) flying in a flight array formation, and (c) swimming on or under liquid. A ground station complements the robotic platform, hosting science instrumentation and providing power to recharge the batteries of the Cobots. Our Phase I study had the objective of providing an initial assessment of the feasibility of the proposed robotic platform architecture, and in particular (a) to characterize the expected science return of a mission to the Sotra-Patera region on Titan; (b) to verify the mechanical and algorithmic feasibility of building a multi-agent platform capable of flying, docking, rolling and un-docking; (c) to evaluate the increased range and efficiency of rolling on Titan w.r.t to flying; (d) to define a case-study of a mission for the exploration of the cryovolcano Sotra-Patera on Titan, whose expected variety of geological features challenges conventional mobility platforms.
In this paper, a novel and innovative methodology for feasible motion planning in the multi-agent system is developed. On the basis of velocity obstacles characteristics, the chance constraints are formulated in the receding horizon control (RHC) pro
We address the problem of maintaining resource availability in a networked multi-robot team performing distributed tracking of unknown number of targets in an environment of interest. Based on our model, robots are equipped with sensing and computati
This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), w
Topology inference is a crucial problem for cooperative control in multi-agent systems. Different from most prior works, this paper is dedicated to inferring the directed network topology from the observations that consist of a single, noisy and fini
Many previous works approach vision-based robotic grasping by training a value network that evaluates grasp proposals. These approaches require an optimization process at run-time to infer the best action from the value network. As a result, the infe