4 papers
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…
Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning
Sigmund Hennum Høeg, Aksel Vaaler, Chaoqi Liu +2
Constructing robots to accomplish long-horizon tasks is a long-standing challenge within artificial intelligence. Approaches using generative methods, particularly Diffusion Models…