arXiv AI
RoboSimStudio: An Interactive Toolkit for Human and Agent Rapid Real2Sim of Robot Manipulation Tasks
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
Hugging Face Trending Papers
Oct 13
RoboSimStudio: An Interactive Toolkit for Rapid Real2Sim of Robot Manipulation Tasks
RoboSimStudio (RSS) is an interactive toolkit designed to simplify the creation of realistic robot manipulation simulations. It allows users to explicitly choose and edit solvers, contact models, and physical parameters, enabling iterative refinement of simulations based on observed behavior. Experiments demonstrate human-guided real-to-sim approaches using visual evaluation, force-feedback, and agentic real-to-sim-to-real methods.
arXiv Computer Vision
Sep 30
Real2Gym: Building Gyms from Videos, Bringing Skills to Robots
arXiv:2609.37089v1 Announce Type: new Abstract: Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, exec...
arXiv AI
Sep 23
Touch2Robot: Robot Touch in the Human Demonstration Loop
arXiv:2609.24660v2 Announce Type: cross Abstract: Human demonstrations offer a scalable way to collect manipulation data, but their contacts may be unstable or infeasible when transferred to a robot...
arXiv AI
Jul 2
Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration
arXiv:2607. 00033v1 Announce Type: cross Abstract: Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging.
arXiv AI
Jul 21
SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-body Manipulation
arXiv:2602. 02402v2 Announce Type: replace-cross Abstract: Simulating deformable objects under rich interactions remains a fundamental challenge for real-to-sim robot manipulation, with dynamics jointly driven by environmental effects and robot actions.
arXiv AI
Sep 25
RAPID: Robot Agentic Programming from Demonstrations
RAPID is a system that automatically generates, verifies, and refines robot programs from a single visual human demonstration. It infers a testable task specification, action primitives, and an interactive environment, using an object-centric relational program representation to enable reuse beyond the demonstration. The approach was evaluated in simulation on eight contact-rich manipulation tasks and successfully deployed on a real Franka arm, showing strong generalization across object pose, shape, material, and environment.