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Optimizing Dynamic Trajectories for Robustness to Disturbances Using Polytopic Projections

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE/RJS International Conference on Intelligent Robots and Systems (IROS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
Publication statusAccepted/In press - 1 Jul 2020
Event2020 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, United States
Duration: 25 Oct 202029 Oct 2020
https://www.iros2020.org/index.html

Conference

Conference2020 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS 2020
CountryUnited States
CityLas Vegas
Period25/10/2029/10/20
Internet address

Abstract

This paper focuses on robustness to disturbance forces and uncertain payloads. We present a novel formulation to optimize the robustness of dynamic trajectories. A straightforward transcription of this formulation into a nonlinear programming problem is not tractable for state-of-the-art solvers, but it is possible to overcome this complication by exploiting the structure induced by the kinematics of the robot. The non-trivial transcription proposed allows trajectory optimization frameworks to converge to highly robust dynamic solutions. We demonstrate the results of our approach using a quadruped robot equipped with a manipulator.

Event

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems

25/10/2029/10/20

Las Vegas, United States

Event: Conference

ID: 160826269