Grasp Planning for Load Sharing in Collaborative Manipulation

Usama Tariq*, Rajkumar Muthusamy, Ville Kyrki

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)
177 Downloads (Pure)


In near future, robots are envisioned to work alongside humans in unstructured professional and domestic environments. In such setups, collaborative manipulation is a fundamental skill that allows manipulation of heavy loads by load sharing between agents. Grasp planning plays a pivotal role for load sharing but it has not received attention in the literature. This work proposes a grasp analysis approach for collaborative manipulation that allows load sharing by minimizing exerted grasp wrenches in a task specific way. The manipulation task is defined as expected external wrenches acting on the target object. The analysis approach is demonstrated in a two-agent decentralized set-up with unknown objects. After the first agent has grasped the target, the second agent observes the first agent's grasp location and plans its own grasp according to optimal load sharing. The method was verified in a human robot collaborative lifting task. Experiments with multiple objects show that the proposed method results in optimal load sharing despite limited information and partial observability.

Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Number of pages8
ISBN (Print)978-1-5386-3081-5
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Robotics and Automation - Brisbane, Australia
Duration: 21 May 201825 May 2018

Publication series

NameIEEE International Conference on Robotics and Automation ICRA
ISSN (Print)1050-4729


ConferenceIEEE International Conference on Robotics and Automation
Abbreviated titleICRA


  • collaborative manipulation
  • manipulation task
  • grasp location
  • human robot collaborative lifting task
  • grasp planning
  • grasp analysis approach
  • load sharing
  • partial observability
  • two-agent decentralized set-up

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