SQP-based mobile manipulator motion planning with controlled infeasibility for physically valid task failure

Chang B. Joo, Joo H. Kim

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

Abstract

Since anticipating or recovering infeasibility in optimal motion planning is not always possible, infeasibilities occur frequently and are not completely avoidable. We introduce an enhanced sequential quadratic programming (SQP) based framework of controlled infeasibility for physically valid solutions, based on our previous study. A priority weight function is incorporated into an SQP algorithm combined with constraints and objective function normalization to ensure strict satisfaction of highpriority constraints. These are embedded in the SQP algorithm through its merit function and composite cost function, in which general nonlinear functions can be incorporated in a unified approach. Several simple mobile manipulator examples demonstrate the advantages of the proposed method.

Original languageEnglish
Title of host publication37th Mechanisms and Robotics Conference
DOIs
StatePublished - 2013
EventASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013 - Portland, OR, United States
Duration: 4 Aug 20137 Aug 2013

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume6 A

Conference

ConferenceASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013
Country/TerritoryUnited States
CityPortland, OR
Period4/08/137/08/13

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