Online Hybrid Motion Planning for Dyadic Collaborative Manipulation via Bilevel Optimization

Effective collaboration is based on online adaptation of one's own actions to the actions of their partner. This article provides a principled formalism to address online adaptation in joint planning problems such as Dyadic collaborative Manipulation (DcM) scenarios. We propose an efficient bil...

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Vydáno v:IEEE transactions on robotics Ročník 36; číslo 5; s. 1452 - 1471
Hlavní autoři: Stouraitis, Theodoros, Chatzinikolaidis, Iordanis, Gienger, Michael, Vijayakumar, Sethu
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptation
Adaptation models
Collaboration
Dual arm manipulation (DaM)
Hybrid power systems
manipulation planning
Motion planning
Optimization
optimization and optimal control
physical human–robot interaction
Planning
Robots
Switches
Task analysis
Trajectory optimization
ISSN:1552-3098, 1941-0468
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Shrnutí:Effective collaboration is based on online adaptation of one's own actions to the actions of their partner. This article provides a principled formalism to address online adaptation in joint planning problems such as Dyadic collaborative Manipulation (DcM) scenarios. We propose an efficient bilevel formulation that combines graph search methods with trajectory optimization, enabling robotic agents to adapt their policy on-the-fly in accordance to changes of the dyadic task. This method is the first to empower agents with the ability to plan online in hybrid spaces; optimizing over discrete contact locations, contact sequence patterns, continuous trajectories, and force profiles for co-manipulation tasks. This is particularly important in large object co-manipulation that requires changes of grasp-holds and plan adaptation. We demonstrate in simulation and with robot experiments the efficacy of the bilevel optimization by investigating the effect of robot policy changes in response to real-time alterations of the dyadic goals, eminent grasp switches, as well as optimal dyadic interactions to realize the joint task.
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2020.2992987