ManiSkill

ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios.

Features

Includes a diverse set of dexterous manipulation tasks and scenarios
Offers both low-dimensional state and high-dimensional visual observations
Supports physics-based simulation using the Isaac Gym engine
Compatible with common RL algorithms and libraries like Stable-Baselines3
Provides standardized benchmarks for robotic manipulation research
Facilitates multi-task learning and generalization across tasks

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Reinforcement Learning Frameworks

Registered

2025-03-13

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