Real Robot Challenge 2021: Cartesian Position Control with Triangle Grasp and Trajectory Interpolation

March 16, 2022 · Entered Twilight · 🏛 arXiv.org

Repo contents: .gitignore, LICENSE, OldREADME.md, README.md, evaluate_policy.py, image.def, log_manager, package.xml, python, resource, run, run_locally.sh, run_locally_bo.sh, run_real_bo, run_real_normal, scripts, setup.cfg, setup.py, tools, training_scripts

Authors Rishabh Madan, Harshit Sikchi, Ethan K. Gordon, Tapomayukh Bhattacharjee arXiv ID 2203.08371 Category cs.RO: Robotics Citations 0 Venue arXiv.org Repository https://github.com/madan96/benchmark-rrc ⭐ 2 Last Checked 3 months ago

Abstract

We present our runner-up approach for the Real Robot Challenge 2021. We build upon our previous approach used in Real Robot Challenge 2020. To solve the task of sequential goal-reaching we focus on two aspects to achieving near-optimal trajectory: Grasp stability and Controller performance. In the RRC 2021 simulated challenge, our method relied on a hand-designed Pinch grasp combined with Trajectory Interpolation for better stability during the motion for fast goal-reaching. In Stage 1, we observe reverting to a Triangular grasp to provide a more stable grasp when combined with Trajectory Interpolation, possibly due to the sim2real gap. The video demonstration for our approach is available at https://youtu.be/dlOueoaRWrM. The code is publicly available at https://github.com/madan96/benchmark-rrc.