1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
IMPACT: Learning Internal-Model Predictive Control for Forceful Robotic Manipulation
Jiawei Gao, Chaoqi Liu, Peilin Wu +2
Real-world robotic manipulation tasks often involve forceful interactions with the environment, such as using tools of varying weights, transporting objects with different masses,…
World Model for Robot Learning: A Comprehensive Survey
Bohan Hou, Gen Li, Jindou Jia +15
World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They support policy learning, planni…
ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation
Yiran Qin, Jiahua Ma, Li Kang +11
Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabling robots to autonomously perf…
Flexible Multitask Learning with Factorized Diffusion Policy
Chaoqi Liu, Haonan Chen, Sigmund H. Høeg +4
Multitask learning poses significant challenges due to the highly multimodal and diverse nature of robot action distributions. However, effectively fitting policies to these comple…