3 papers
cs.RO2024
Visual Imitation Learning of Task-Oriented Object Grasping and Rearrangement
Yichen Cai, Jianfeng Gao, Christoph Pohl +1
Task-oriented object grasping and rearrangement are critical skills for robots to accomplish different real-world manipulation tasks. However, they remain challenging due to partia…
cs.RO2024
AutoGPT+P: Affordance-based Task Planning with Large Language Models
Timo Birr, Christoph Pohl, Abdelrahman Younes +1
Recent advances in task planning leverage Large Language Models (LLMs) to improve generalizability by combining such models with classical planning algorithms to address their inhe…
cs.RO2024
MAkEable: Memory-centered and Affordance-based Task Execution Framework for Transferable Mobile Manipulation Skills
Christoph Pohl, Fabian Reister, Fabian Peller-Konrad +1
To perform versatile mobile manipulation tasks in human-centered environments, the ability to efficiently transfer learned tasks and experiences from one robot to another or across…