The transparent interaction between an operator and a robot system is essential for successful task completion. This requires a mutual understanding of decisions and processes in order to provide accurate diagnoses and troubleshooting alternatives in the event of a failure. Due to inaccuracies in the environmental perception or planner configuration, errors can occur in robot motion planning that are hard to understand by the operator. In this work we present a method that is able to provide explanations for motion planning failures quickly. In the context of optimization-based planners, failures origin from planning constraints can be identified using an adaption of the FastDiag algorithm. It is able to provide one preferred minimal diagnosis in logarithmic time, also for large constraint sets. To evaluate the applicability of the proposed method, experiments are conducted that compare the computational performance to an existing method while considering different parameters such as number of constraints and requested diagnoses.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Fast Method for Explanations of Failures in Optimization-Based Robot Motion Planning


    Additional title:

    Mechan. Machine Science



    Conference:

    International Conference on Robotics in Alpe-Adria Danube Region ; 2022 ; Klagenfurt, Austria June 08, 2022 - June 10, 2022



    Publication date :

    2022-04-23


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    A Fast Method for Explanations of Failures in Optimization-Based Robot Motion Planning

    Eder, Matthias / Steinbauer-Wagner, Gerald | TIBKAT | 2022


    Robot formation motion planning using Fast Marching

    Garrido Bullón, Luis Santiago / Moreno Lorente, Luis Enrique / Lima, Pedro U. | BASE | 2011

    Free access


    A NOVEL FAST MOTION PLANNING ALGORITHM FOR SPACE REDUNDANT ROBOT

    Li, Jie / Zhu, Zhanxia / Zhong, Jianfei et al. | TIBKAT | 2022


    Verbal explanations by collaborating robot teams

    Singh, Avinash / Baranwal, Neha / Richter, Kai-Florian et al. | BASE | 2021

    Free access