MorphAct: Robot Policies Morphing with the Worlds They Act In
cs.RO, cs.AI
Submitted: 2026-10-14
Updated: 2026-10-14
Comments: 25 pages. Project page: https://mint-sjtu.github.io/MorphAct.io/
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
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
- ARC: A Reasoning Recipe for Robot Foundation Models
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies