A Lightweight and Transferable Design for Robust LEGO Manipulation

TL;DR

This paper presents a hardware-software co-designed, lightweight robotic system for precise and transferable Lego manipulation, achieving high success rates and demonstrating generalizability across different industrial robots.

Contribution

It introduces a novel EOAT and an evolution strategy-based learning framework for efficient Lego manipulation, enhancing transferability and safety in robotic prototyping.

Findings

Achieved 100% success rate in Lego manipulation tasks.

Demonstrated transferability across multiple industrial robot models.

Enabled sustainable and repeatable Lego prototyping.

Abstract

Lego is a well-known platform for prototyping pixelized objects. However, robotic Lego prototyping (i.e., manipulating Lego bricks) is challenging due to the tight connections and accuracy requirements. This paper investigates safe and efficient robotic Lego manipulation. In particular, this paper reduces the complexity of the manipulation by hardware-software co-design. An end-of-arm tool (EOAT) is designed, which reduces the problem dimension and allows large industrial robots to manipulate small Lego bricks. In addition, this paper uses evolution strategy to optimize the robot motion for Lego manipulation. Experiments demonstrate that the EOAT can reliably manipulate Lego bricks and the learning framework can effectively and safely improve the manipulation performance to a 100% success rate. The co-design is deployed to multiple robots (i.e., FANUC LR-mate 200id/7L and Yaskawa GP4) to demonstrate its generalizability and transferability. In the end, we show that the proposed solution enables sustainable robotic Lego prototyping, in which the robot can repeatedly assemble and disassemble different prototypes.