Improving Human-Robot Collaboration via Computational Design

Abstract

When robots enter our day-to-day lives, the shared space surrounding humans and robots is critical for facilitating Human-Robot collaboration. The design of shared space should satisfy humans' preferences and robots' efficiency. This work uses the kitchen as an example to illustrate the importance of good space designs in enhancing collaboration. Given the kitchen boundary, food stations, counters, and recipes, the proposed method determines the optimal placement of stations and counters that meet the requirements of kitchen design rules and improve performance. The key technical challenge is that the optimization method usually evaluates thousands of designs, and each evaluation analyzes the traffic flow of the space, which must solve many motion planning problems. To address this technical challenge, we use a decentralized motion planner that can solve multi-agent motion planning efficiently. Our results indicate that optimized kitchen designs can provide noticeable performance improvement to Human-Robot collaboration.