maniskill

🔥 [ICLR 2026] Benchmark for robotic tabletop manipulation memory-intensive tasks

Squint: Fast Visual Reinforcement Learning for Sim-to-Real Robotics [PyTorch, SO-101 Robot Arm, ManiSkill3, Sim-to-Real]

🔥[AAMAS 2026 Oral] Don’t Blind Your VLA: Aligning Visual Representations for OOD Generalization. https://blind-vla-paper.github.io

Official implementation of "Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories" (ENAP, RSS 2026): neuro-symbolic imitation learning that learns task structure from demonstrations as a state machine.

A minimal Vision-Language-Action model you can read: frozen CLIP + a tiny head on ManiSkill PickCube. LeRobot integration. Runs on a Mac, no GPU.

APPL is an agentic robot learning framework connecting policy learning with agent-based skill selection and composition through structural priors for generalization from a few demonstrations to new scenes and task compositions.

Minimum example showing how to setup Singularity with Maniskill3 to run training headless on a cluster.

Asset files for the Trossen Robotics WidowX AI robot for the ManiSkill framework

Benchmark for adaptation to hidden robot action-interface contracts: 4 ManiSkill tasks, preregistered gates, belief/probe/learned methods, delay-aware control. Same policy, different wiring — can it adapt?

RAIN: Refine Actions If Needed — adaptive action chunk refinement for robot manipulation (arXiv:2610.19765).

PPO reinforcement learning on the Unitree G1 humanoid — learning bipedal balance in MuJoCo and dexterous apple-in-bowl manipulation in ManiSkill 3, with side-by-side training-progression demos.

Self-hosted robotics workflow workbench: simulation integrations, dataset tools, training and artifact provenance. Alpha; trusted-local use.

Training and deploying ACT policies for SO-101 cube grasping: motion-planning data collection, ManiSkill-to-LeRobot conversion, then simulation and real-robot evaluation.

Coverage-driven edge-case hunting for robot policies: to ensure your robot policies have four-ninges reliability

Reproducible ManiSkill PickCube visual imitation-learning workflow for MLP BC and ACT.

Predicted Futures Are Not Enough: Learning Executable Goals for Robot Manipulation — code, frozen goal banks and evaluation records

Reproducible comparisons of open robotics AI models, data pipelines, simulators, and contribution workflows

GPU-parallel visual PPO for ManiSkill StackCube: asymmetric Actor-Critic, four-frame dual-camera input, normalization, TCAPS and NoEarlyReset.

双相机 Qwen3.5 VLA：可信数据、Rectified Flow Action Chunk、ManiSkill 闭环评估与 temporal ensemble

Tight-clearance insertion demonstrations in ManiSkill: 4cm cube into a 4.2cm tray cell, and a phone into a slot via two-Panda handoff. Collected for PI0.5/VLA training.