Multi-Modal Multi-Agent Optimization for LIMMS, A Modular Robotics Approach to Delivery Automation

TL;DR

This paper introduces a motion planning approach for LIMMS, a modular multi-agent robotic system capable of multi-modal operations, using ADMM optimization to coordinate diverse roles for delivery tasks.

Contribution

It presents a novel multi-modal motion planner for LIMMS, enabling complex coordination among heterogeneous modules for delivery automation.

Findings

Successfully demonstrated multi-modal capabilities in various scenarios

Effective optimization of multi-agent coordination using ADMM

LIMMS can adapt roles dynamically to achieve delivery goals

Abstract

In this paper we present a motion planner for LIMMS, a modular multi-agent, multi-modal package delivery platform. A single LIMMS unit is a robot that can operate as an arm or leg depending on how and what it is attached to, e.g., a manipulator when it is anchored to walls within a delivery vehicle or a quadruped robot when 4 are attached to a box. Coordinating amongst multiple LIMMS, when each one can take on vastly different roles, can quickly become complex. For such a planning problem we first compose the necessary logic and constraints. The formulation is then solved for skill exploration and can be implemented on hardware after refinement. To solve this optimization problem we use alternating direction method of multipliers (ADMM). The proposed planner is experimented under various scenarios which shows the capability of LIMMS to enter into different modes or combinations of them to achieve their goal of moving shipping boxes.