Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation
cs.RO
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: Accepted at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models
- Octo: An Open-Source Generalist Robot Policy
- Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation
- Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers
- OpenBot-Fleet: A System for Collective Learning with Real Robots
- Robot Fleet Learning via Policy Merging
- Masked Trajectory Models for Prediction, Representation, and Control
- CLASS: Contrastive Learning via Action Sequence Supervision for Robot Manipulation
- Latent Diffusion Planning for Imitation Learning
- TD-MPC2: Scalable, Robust World Models for Continuous Control
- Mastering Diverse Domains through World Models
- Multi-Task Interactive Robot Fleet Learning with Visual World Models
- Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space Alignment
- Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting
- One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
- Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation
- Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation
- Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
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