1 citations · 2 across the 5 of their papers we have counts for
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Interactive Human-in-the-loop Coordination of Manipulation Skills Learned from Demonstration
Meng Guo, Mathias Buerger
Learning from demonstration (LfD) provides a fast, intuitive and efficient framework to program robot skills, which has gained growing interest both in research and industrial appl…
Geometric Task Networks: Learning Efficient and Explainable Skill Coordination for Object Manipulation
Meng Guo, Mathias Bürger
Complex manipulation tasks can contain various execution branches of primitive skills in sequence or in parallel under different scenarios. Manual specifications of such branching…
Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks
Leonel Rozo, Meng Guo, Andras G. Kupcsik +8
Enabling robots to quickly learn manipulation skills is an important, yet challenging problem. Such manipulation skills should be flexible, e.g., be able adapt to the current works…
Human-in-the-Loop Mixed-Initiative Control under Temporal Tasks
Meng Guo, Sofie Andersson, Dimos V. Dimarogonas
This paper considers the motion control and task planning problem of mobile robots under complex high-level tasks and human initiatives. The assigned task is specified as Linear Te…
Probabilistic Motion Planning under Temporal Tasks and Soft Constraints
Meng Guo, Michael M. Zavlanos
This paper studies motion planning of a mobile robot under uncertainty. The control objective is to synthesize a {finite-memory} control policy, such that a high-level task specifi…