Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation (arXiv 2609.01596)
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Updated
Oct 20, 2026 - Python
Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation (arXiv 2609.01596)
Related paper: "Experimental Validation of an Actor-Critic Model Predictive Force Controller for Robot-Environment Interaction Tasks"
An admittance controller for the Reach Bravo 7 manipulator.
Does tactile prediction help? ImplicitRDP + a hard-coded normal-force loop in TacSL sim: measured vs predicted vs true pressure, noise curve, probes, video
Diploma thesis concerning the development of a force sensory system for a small fabric gripper and formation control of two wheeled mobile robots based on fabric force feedback
An open-source wall sanding and finishing robot. Force-controlled sanding in MuJoCo, with a dry-rehearsed real-arm stack.
Doosan M0609 도미노 적층·전도 — 힘 제어 + 베지어 경로 보간
NVIDIA Isaac Sim keyboard teleoperation and force-controlled grasping for UR5/UR5e using Lula IK, RG2-FT force/torque sensing, and fingertip lidar.
Seating a gasket cord into a channel: force regulation with a real tolerance spec — a task the standard benchmarks lack. MuJoCo.
PreWash-Cell — 카메라 없이 파지 폭 · 무게 · 힘만으로 다회용기를 닦아 식기세척기에 꽂는 협동로봇 셀 (ROS 2 · Doosan M0609 · FastAPI · Next.js)
Force-guided peg-in-hole contact preparation and PPO search experiments in MJLab
Model-based motion and force control for UR3 + FT300 using Pinocchio, MuJoCo and TSID/HQP.
Reinforcement learning for block stacking on a UR7e: MuJoCo replica of the lab cell, residual PPO (83% of towers), end-to-end PPO curriculum, ROS 2 node running the policy on the real arm
Autonomous fiber-optic cable insertion with a UR5e in simulation: board registration, learned SFP and SC port detection, multi-camera fusion and contact-based seating. My qualification-phase entry for Intrinsic’s AI for Industry Challenge, built on ROS 2 and PyTorch.
두산 로보틱스 Rokey 9기 협동1 프로젝트 D2팀 — PreWash-Cell: 협동로봇 다회용기 예비세척 자동화 셀 (개인 포트폴리오판)
Interactive Franka writing digital twin with freehand/SVG input, hybrid Cartesian force control, differential IK, live telemetry, PyBullet, Pinocchio, Docker, CI, and quantitative V&V.
Franka 7-DOF compliant-control lab: impedance, adaptive hybrid control, torque-safe Residual RL, C++ parity, and blinded MuJoCo evaluation.
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