IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Youngwoon Lee, Edward S. Hu, Joseph J. Lim
Abstract
The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of long-horizon and hierarchical manipulation tasks. The environment is designed to advance reinforcement learning and imitation learning from simple toy tasks to complex tasks requiring both long-term planning and sophisticated low-level control. Our environment features 60 furniture models, 6 robots, photorealistic rendering, and domain randomization. We evaluate reinforcement learning and imitation learning methods on the proposed environment. Our experiments show furniture assembly is a challenging task due to its long horizon and sophisticated manipulation requirements, which provides ample opportunities for future research. The environment is publicly available at https://clvrai.com/furniture.