3 citations · 4 across the 7 of their papers we have counts for
7 papers
CDCP: Conditional Diffusion Model with Contextual Prompts for Multi-task Offline Safe Reinforcement Learning
Jiayi Guan, Tianle Zhang, Li Shen +8
Multi-task offline safe reinforcement learning (RL) promises to learn a shared optimal safe policy from offline data across multiple tasks. This paradigm provides an effective mean…
Object-Focus Actor for Data-efficient Robot Generalization Dexterous Manipulation
Yihang Li, Tianle Zhang, Xuelong Wei +7
Robot manipulation learning from human demonstrations offers a rapid means to acquire skills but often lacks generalization across diverse scenes and object placements. This limita…
Dexterous Grasping with Real-World Robotic Reinforcement Learning
Dongchi Huang, Tianle Zhang, Yihang Li +5
Dexterous grasping in the real world presents a fundamental and significant challenge for robot learning. The ability to employ affordance-aware poses to grasp objects with diverse…
An Atomic Skill Library Construction Method for Data-Efficient Embodied Manipulation
Dongjiang Li, Bo Peng, Chang Li +13
Embodied manipulation is a fundamental ability in the realm of embodied artificial intelligence. Although current embodied manipulation models show certain generalizations in speci…
Empowering Embodied Manipulation: A Bimanual-Mobile Robot Manipulation Dataset for Household Tasks
Tianle Zhang, Dongjiang Li, Yihang Li +8
The advancements in embodied AI are increasingly enabling robots to tackle complex real-world tasks, such as household manipulation. However, the deployment of robots in these envi…
Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
Tianle Zhang, Jiayi Guan, Lin Zhao +8
Offline reinforcement learning (RL) aims to learn optimal policies from previously collected datasets. Recently, due to their powerful representational capabilities, diffusion mode…
Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld
Yijun Yang, Tianyi Zhou, Kanxue Li +6
While large language models (LLMs) excel in a simulated world of texts, they struggle to interact with the more realistic world without perceptions of other modalities such as visu…