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Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses

2026-10-15 16:57:17
Wei Wang (Robostreet research team. Cambridge, MA, USA), Yiru Veronika Wang (Robostreet research team. Cambridge, MA, USA), Yihan Wang (Robostreet research team. Cambridge, MA, USA), Zihao Li (Robostreet research team. Cambridge, MA, USA), Xiaohui Liang (Robostreet research team. Cambridge, MA, USA)

Abstract

Refuse collection in pedestrian campuses, parks and mixed-use districts remains manual because compaction trucks cannot reach bins located on walkways, courtyards and building service doors. This paper presents Mothership, a two-tier autonomous refuse collection system in which an electric compaction truck (the mothership) carries two low-speed sidewalk robots (RoboCarts) that fetch standard two-wheel bins, deliver them to the truck, return the empty bins to their original positions and re-dock on the truck for charging. The architecture separates responsibilities by scale: the truck performs road driving, compaction, lifting and energy supply, while the carts perform only sidewalk transport and bin grasping. This split removes the lift-and-tip mechanism from the sidewalk vehicle, keeping it light and low, and relaxes cart-to-truck docking tolerance to the +/-100 mm capture window of a standard automated lifter. We describe the system architecture, the bin-handling and docking interfaces, and a mission-planning formulation that decomposes a route into truck stop points and cart tasks. A discrete-event simulation over synthetic campus layouts with 2-16 bins/ha quantifies throughput as a function of bin density, cart count and stop-point radius. A two-cart configuration serves 20-29 bins/h. Throughput is governed by an interaction between cart count and stop-point radius: a single cart performs best with many close stops, whereas three or four carts need wide stops (80 m) to stay busy, reaching 35-49 bins/h at moderate-to-high densities. The best stop radius therefore has to be chosen together with the fleet size, not fixed in advance.

Abstract (translated)

URL

https://arxiv.org/abs/2610.22461

PDF

https://arxiv.org/pdf/2610.22461.pdf


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