Robot-GST: geometry-aware spatial-temporal robot policy representation and evaluation
cs.RO, cs.AI, cs.LG
Submitted: 2026-09-27
Updated: 2026-09-27
Project page: https://robot-gst.github.io
Terminology
Sources
- Octo: An Open-Source Generalist Robot Policy
- OpenVLA: An Open-Source Vision-Language-Action Model
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
- Difficulty-Estimated Policy Optimization
- Real-to-Sim Robot Policy Evaluation with Gaussian Splatting Simulation of Soft-Body Interactions
- ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
- MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting
- RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics
- Vision Language Action Models in Robotic Manipulation: A Systematic Review
- GraspSplats: Efficient Manipulation with 3D Feature Splatting
- Reliable and Scalable Robot Policy Evaluation with Imperfect Simulators
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- Inner Monologue: Embodied Reasoning through Planning with Language Models
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Related papers
- FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
- MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
- RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving