stepjam/RLBench resource

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1811 stars · 321 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

RLBench is a large-scale robot learning benchmark and simulation environment built on CoppeliaSim and PyRep, featuring 100 hand-designed manipulation tasks. It supports research in vision-guided manipulation including reinforcement learning, imitation learning, multi-task learning, and few-shot learning.

Use cases

• benchmark robot manipulation policies in simulation
• train reinforcement learning agents on robotic tasks
• collect demonstrations for imitation learning
• run multi-task and few-shot meta-learning experiments
• evaluate vision-guided grasping and manipulation
• build custom robot manipulation tasks

When to choose

• you need a diverse set of simulated manipulation tasks with ground-truth data
• you research RL, imitation learning, or few-shot learning for robotics
• you want a Gym-compatible robot learning environment

When to avoid

• you need real-robot hardware experiments only
• you work outside Linux or cannot install CoppeliaSim
• you need lightweight or non-robotics simulation

Facets

dataset · maturity active

simulation machine-learning reinforcement-learning computer-vision benchmarking robotics reinforcement-learning machine-learning computer-vision simulation python robot-learning manipulation imitation-learning benchmark coppeliasim few-shot-learning gym-environment linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="stepjam/RLBench")