ROLGNESep 5, 2023

A Lightweight and Transferable Design for Robust LEGO Manipulation

arXiv:2309.02354v313 citationsh-index: 14
Originality Incremental advance
AI Analysis

This work addresses the problem of efficient and safe robotic prototyping with Lego bricks, which is incremental as it builds on existing robotic manipulation methods.

The paper tackled the challenge of robotic Lego manipulation by developing a hardware-software co-design, including an end-of-arm tool and motion optimization using evolution strategy, achieving a 100% success rate in experiments.

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.

Foundations

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