Description

This PR introduces a new Gear Assembly manipulation task for sim-to-real training with the UR10e robot arm. This environment enables training policies for precise gear insertion tasks using reinforcement learning, with comprehensive sim-to-real transfer capabilities.

Summary of Changes

New Features

• Gear Assembly Environment: Complete environment implementation for gear insertion tasks

  • Environment configuration (gear_assembly_env_cfg.py)
  • UR10e-specific joint position control configuration (joint_pos_env_cfg.py)
  • RSL-RL PPO training configuration (rsl_rl_ppo_cfg.py)

• MDP Components: Task-specific observation, reward, termination, and event functions

  • mdp/events.py: Randomization and reset events for robust training
  • mdp/observations.py: State observation functions
  • mdp/rewards.py: Reward shaping for gear insertion
  • mdp/terminations.py: Episode termination conditions

• Noise Models: Enhanced noise simulation for domain randomization

  • Added configurable noise models (noise_model.py, noise_cfg.py)
  • Integration with observation and action spaces for realistic sim-to-real transfer

Documentation

• Sim-to-Real Training Walkthrough: Complete guide for training and deploying the gear assembly task
  • Step-by-step training instructions
  • Real robot deployment guidelines
  • Visual assets (GIFs and screenshots)

Core Enhancements

• Training Script: Enhanced train.py with additional logging and configuration options
• UR10e Robot Configuration: Updated universal_robots.py with gear assembly specific parameters
• Reward System: Extended core reward functions in isaaclab/envs/mdp/rewards.py
• RL Configuration: Updated RSL-RL integration (rl_cfg.py, setup.py)

Type of change

• New feature (non-breaking change which adds functionality)
• Documentation update

Checklist

• I have read and understood the contribution guidelines
• I have run the pre-commit checks with ./isaaclab.sh --format
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• I have updated the changelog and the corresponding version in the extension's config/extension.toml file
• I have added my name to the CONTRIBUTORS.md or my name already exists there

Usage Example

# Train the gear assembly task
python scripts/reinforcement_learning/rsl_rl/train.py \
  --task Isaac-Deploy-GearAssembly-UR10e-2F140-v0 \
  --num_envs 256 \
  --headless

# Run inference with trained policy
python scripts/reinforcement_learning/rsl_rl/play.py \
  --task Isaac-Deploy-GearAssembly-UR10e-2F140-v0 \
  --num_envs 1 \
 --checkpoint <checkpoint_path>