異種マルチロボットのための耐障害性・省エネ型タスク割当フレームワーク
A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systems
異種ロボットチームが複数タスクを長時間自律実行するため、消費エネルギー最小化の最適化問題としてタスク割当をオンラインで行い、環境変化や故障にも耐える枠組みを提案・実機検証した。
著者: Gennaro Notomista, Siddharth Mayya, Yousef Emam, Christopher Kroninger, Addison Bohannon, Seth Hutchinson, Magnus Egerstedt
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In the context of heterogeneous multi-robot teams deployed for executing multiple tasks, this paper develops an energy-aware framework for allocating tasks to robots in an online fashion. With a primary focus on long-duration autonomy applications, we opt for a survivability-focused approach. Towards this end, the task prioritization and execution -- through which the allocation of tasks to robots is effectively realized -- are encoded as constraints within an optimization problem aimed at minimizing the energy consumed by the robots at each point in time. In this context, an allocation is interpreted as a prioritization of a task over all others by each of the robots. Furthermore, we present a novel framework to represent the heterogeneous capabilities of the robots, by distinguishing between the features available on the robots, and the capabilities enabled by these features. By embedding these descriptions within the optimization problem, we make the framework resilient to situations where environmental conditions make certain features unsuitable to support a capability and when component failures on the robots occur. We demonstrate the efficacy and resilience of the proposed approach in a variety of use-case scenarios, consisting of simulations and real robot experiments.
