Matches in SemOpenAlex for { <https://semopenalex.org/work/W3080772040> ?p ?o ?g. }
- W3080772040 endingPage "1110" @default.
- W3080772040 startingPage "1100" @default.
- W3080772040 abstract "In this article, we address the trajectory tracking problem using the learning from demonstration (LFD) method. By using the LFD method, the parameter adjusting problem in the tracking controller is avoided. Consequently, a strategy can be provided to users with limited parameter adjusting experience. The kinematic tracking problem is formulated as a second-order system and the objective is to simultaneously reduce the errors in position and velocity. The extreme learning machines (ELM) algorithm is applied in the controller design. The velocity and position are utilized as the inputs and the output is the robot corrected kinematic movement. The controller parameters are learned from the desired human or programming demonstrations taking into consideration the stability constraints. In this work, we analyze the system local and global asymptotic stability in detail. The effectiveness of the proposed strategy is demonstrated by simulation comparisons and a practical experiment using a KUKA robot manipulator." @default.
- W3080772040 created "2020-09-01" @default.
- W3080772040 creator A5019560977 @default.
- W3080772040 creator A5028561947 @default.
- W3080772040 creator A5065142478 @default.
- W3080772040 creator A5066181483 @default.
- W3080772040 creator A5089568886 @default.
- W3080772040 date "2022-02-01" @default.
- W3080772040 modified "2023-10-11" @default.
- W3080772040 title "Learning-Based Kinematic Control Using Position and Velocity Errors for Robot Trajectory Tracking" @default.
- W3080772040 cites W1980194129 @default.
- W3080772040 cites W1986014385 @default.
- W3080772040 cites W1991667713 @default.
- W3080772040 cites W2008491851 @default.
- W3080772040 cites W2050176043 @default.
- W3080772040 cites W2104171826 @default.
- W3080772040 cites W2105686579 @default.
- W3080772040 cites W2107664584 @default.
- W3080772040 cites W2111072639 @default.
- W3080772040 cites W2129202194 @default.
- W3080772040 cites W2138484437 @default.
- W3080772040 cites W2144063905 @default.
- W3080772040 cites W2171438612 @default.
- W3080772040 cites W2200971133 @default.
- W3080772040 cites W2284232578 @default.
- W3080772040 cites W2336820608 @default.
- W3080772040 cites W2364918774 @default.
- W3080772040 cites W2388591084 @default.
- W3080772040 cites W2744687549 @default.
- W3080772040 cites W2765519151 @default.
- W3080772040 cites W2766381601 @default.
- W3080772040 cites W2883972132 @default.
- W3080772040 cites W2884876207 @default.
- W3080772040 cites W2885017279 @default.
- W3080772040 cites W2891765131 @default.
- W3080772040 cites W2913764430 @default.
- W3080772040 cites W2940956030 @default.
- W3080772040 cites W2942510244 @default.
- W3080772040 cites W2946234510 @default.
- W3080772040 cites W2946250619 @default.
- W3080772040 cites W2963476895 @default.
- W3080772040 cites W2984769036 @default.
- W3080772040 cites W3098105401 @default.
- W3080772040 cites W3100966471 @default.
- W3080772040 cites W4240552839 @default.
- W3080772040 doi "https://doi.org/10.1109/tsmc.2020.3013904" @default.
- W3080772040 hasPublicationYear "2022" @default.
- W3080772040 type Work @default.
- W3080772040 sameAs 3080772040 @default.
- W3080772040 citedByCount "10" @default.
- W3080772040 countsByYear W30807720402022 @default.
- W3080772040 countsByYear W30807720402023 @default.
- W3080772040 crossrefType "journal-article" @default.
- W3080772040 hasAuthorship W3080772040A5019560977 @default.
- W3080772040 hasAuthorship W3080772040A5028561947 @default.
- W3080772040 hasAuthorship W3080772040A5065142478 @default.
- W3080772040 hasAuthorship W3080772040A5066181483 @default.
- W3080772040 hasAuthorship W3080772040A5089568886 @default.
- W3080772040 hasConcept C10138342 @default.
- W3080772040 hasConcept C112972136 @default.
- W3080772040 hasConcept C119857082 @default.
- W3080772040 hasConcept C121332964 @default.
- W3080772040 hasConcept C127413603 @default.
- W3080772040 hasConcept C1276947 @default.
- W3080772040 hasConcept C133731056 @default.
- W3080772040 hasConcept C13662910 @default.
- W3080772040 hasConcept C154945302 @default.
- W3080772040 hasConcept C15744967 @default.
- W3080772040 hasConcept C162324750 @default.
- W3080772040 hasConcept C183356978 @default.
- W3080772040 hasConcept C19417346 @default.
- W3080772040 hasConcept C198082294 @default.
- W3080772040 hasConcept C203479927 @default.
- W3080772040 hasConcept C2775924081 @default.
- W3080772040 hasConcept C2775936607 @default.
- W3080772040 hasConcept C39920418 @default.
- W3080772040 hasConcept C41008148 @default.
- W3080772040 hasConcept C47446073 @default.
- W3080772040 hasConcept C6557445 @default.
- W3080772040 hasConcept C74650414 @default.
- W3080772040 hasConcept C86803240 @default.
- W3080772040 hasConcept C90509273 @default.
- W3080772040 hasConceptScore W3080772040C10138342 @default.
- W3080772040 hasConceptScore W3080772040C112972136 @default.
- W3080772040 hasConceptScore W3080772040C119857082 @default.
- W3080772040 hasConceptScore W3080772040C121332964 @default.
- W3080772040 hasConceptScore W3080772040C127413603 @default.
- W3080772040 hasConceptScore W3080772040C1276947 @default.
- W3080772040 hasConceptScore W3080772040C133731056 @default.
- W3080772040 hasConceptScore W3080772040C13662910 @default.
- W3080772040 hasConceptScore W3080772040C154945302 @default.
- W3080772040 hasConceptScore W3080772040C15744967 @default.
- W3080772040 hasConceptScore W3080772040C162324750 @default.
- W3080772040 hasConceptScore W3080772040C183356978 @default.
- W3080772040 hasConceptScore W3080772040C19417346 @default.
- W3080772040 hasConceptScore W3080772040C198082294 @default.
- W3080772040 hasConceptScore W3080772040C203479927 @default.
- W3080772040 hasConceptScore W3080772040C2775924081 @default.