异构机器人团队用接力式负载均衡，无需中央控制也能高效协作。
Pass the Bucket: Efficient, Robust, Local Load Balancing for Teams of Heterogeneous Robots
- 通过局部感应碰撞和令牌机制实现无中心负载均衡。
- 系统在扰动下仍能快速收敛，稳定状态符合机器人速度比例的区间分配。
- 适合复杂场景下异构机器人团队的自组织任务分配。
我们研究异构机器人团队在受限一维空间中进行运输等协同任务时的去中心化、自组织任务分配问题。提出基于‘接力桶’机制的简单有效负载均衡方法，机器人仅通过感知邻近碰撞或墙壁来协作，目标是优化整体吞吐量，实现与机器人速度成比例的区间划分。为防止系统出现混沌行为，引入基于局部援助的稳定机制——‘令牌’，在机器人相遇后临时减速。该纯局部调整可消除持续振荡，使系统收敛至稳定状态。通过对比单边界令牌与双向普遍令牌，并优化减速因子，加速收敛。事件驱动仿真显示，系统对多种扰动（如机器人删除、位置或速度抖动）具有强鲁棒性，能可靠重新收敛。结果表明，该机制为异构机器人团队提供了实用、稳健的负载均衡方案，可作为更复杂场景的基础。
原文摘要 · Abstract (English)
We study the problem of decentralized, self-organized task sharing for a swarm of heterogeneous robots that collaborate in transportation or other objectives that require coordinated motion planning. To this end, we present theoretical and practical results for the simple but effective mechanism of \emph{bucket brigades} for load balancing, in which a team of heterogenous robots share a spatial task in a confined, one-dimensional space, while only being able to sense collisions with neighbors or walls. The goal is to optimize throughput of the overall system, without central control or information, aiming at an interval partition proportional to robot velocities. We address possible chaotic system behavior by developing a stabilization mechanism based on simple local aid, a ``token'', that temporarily decelerates robots after an encounter. This purely local change eliminates persistent oscillations, resulting in convergence towards a stable system state. We accelerate system convergence by comparing a single boundary token to ubiquitous two-directional tokens and optimizing the deceleration factor. Event-driven simulations report convergence times and robustness: For a large variety of perturbations (such as robot deletion, position or velocity jittering), the system reliably re-converges. The results suggest a local, practical mechanism for robust load balancing for heterogeneous teams of robots that promises an effective tool as basis for more complex scenarios.
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