Skip to main content
archive
Search Submit Donate Log in
Press Enter to search · Advanced search

Computer Science > Robotics

arXiv:2006.03614 (cs)
[Submitted on 5 Jun 2020 (v1), last revised 31 Jul 2020 (this version, v2)]

Title:Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization

Authors:Abhinav Jain, Daphne Chen, Dhruva Bansal, Sam Scheele, Mayank Kishore, Hritik Sapra, David Kent, Harish Ravichandar, Sonia Chernova
View a PDF of the paper titled Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization, by Abhinav Jain and 8 other authors
View PDF HTML (experimental)
Abstract:We address the problem of adapting robot trajectories to improve safety, comfort, and efficiency in human-robot collaborative tasks. To this end, we propose CoMOTO, a trajectory optimization framework that utilizes stochastic motion prediction models to anticipate the human's motion and adapt the robot's joint trajectory accordingly. We design a multi-objective cost function that simultaneously optimizes for i) separation distance, ii) visibility of the end-effector, iii) legibility, iv) efficiency, and v) smoothness. We evaluate CoMOTO against three existing methods for robot trajectory generation when in close proximity to humans. Our experimental results indicate that our approach consistently outperforms existing methods over a combined set of safety, comfort, and efficiency metrics.
Comments: To be published at the International Conference on Intelligent Robots and Systems (IROS), 2020
Subjects: Robotics (cs.RO)
Cite as: arXiv:2006.03614 [cs.RO]
  (or arXiv:2006.03614v2 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2006.03614
arXiv-issued DOI via DataCite

Submission history

From: Abhinav Jain [view email]
[v1] Fri, 5 Jun 2020 18:09:01 UTC (2,949 KB)
[v2] Fri, 31 Jul 2020 00:14:07 UTC (5,530 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization, by Abhinav Jain and 8 other authors
  • View PDF
  • HTML (experimental)
  • TeX Source
view license

Current browse context:

cs.RO
< prev   |   next >
new | recent | 2020-06
Change to browse by:
cs

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar

DBLP - CS Bibliography

listing | bibtex
Harish Ravichandar
Sonia Chernova
Loading...

BibTeX formatted citation

Data provided by:

Bookmark

BibSonomy Reddit

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
We gratefully acknowledge support from our major funders, member institutions, , and all contributors.
About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)
Major funding support from
Simons Foundation Simons Foundation International Schmidt Sciences