MimicKit: A Reinforcement Learning Framework for Motion Imitation and Control
This framework addresses the need for standardized tools in motion imitation and control for researchers and practitioners, but it is incremental as it builds on existing techniques.
The authors introduced MimicKit, an open-source reinforcement learning framework for training motion controllers, providing a unified and modular codebase to support research in computer graphics and robotics.
MimicKit is an open-source framework for training motion controllers using motion imitation and reinforcement learning. The codebase provides implementations of commonly-used motion-imitation techniques and RL algorithms. This framework is intended to support research and applications in computer graphics and robotics by providing a unified training framework, along with standardized environment, agent, and data structures. The codebase is designed to be modular and easily configurable, enabling convenient modification and extension to new characters and tasks. The open-source codebase is available at: https://github.com/xbpeng/MimicKit.