As robots become increasingly prevalent in society, it is essential to prescribe complex high-level tasks to them. Tasks prescribed over temporal logics present two main challenges: generating trajectories that satisfy the logical formula and tracking those trajectories that depend on the logical formula. This thesis aims to address these challenges. Firstly, we use Prescribed Performance Control (PPC) to solve the cooperative manipulation problem based on constraints defined by an Signal Temporal Logic (STL) formula. Secondly, we design a planning algorithm that generates spatio-temporal trees and searches for trajectories that satisfy an STL formula for cooperating agents. Finally, we utilise gradient-based methods to shape trajectories that satisfy an STL formula for multiple cooperating agents. Our approach is based on integration of tools from the areas of multi-agent systems, optimisation theory, cooperative object manipulation and motion planning. More specifically, in the second chapter we start by focusing on solving the problem of cooperative manipulation of an object specified by an STL formula. To achieve this, we utilise the PPC methodology, which enforces the desired transient and steady-state performance on the object trajectory to satisfy the STL formula. Specifically, we propose a method that translates the problem of satisfying an STL task into the problem of state evolution within a custom-defined time-varying funnel, which is then used to design a decentralised control strategy for robotic agents. The strategy guarantees compliance with the funnel, and each agent calculates its own control signal, without utilising any information on the dynamic terms of the agents or object. We provide experimental validation of our approach using two manipulator arms cooperatively manipulating an object based on a specified STL formula. In the next chapter, we present a novel motion planning algorithm for two autonomous agents working together to accomplish coupled tasks expressed as STL constraints. The ...


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    Titel :

    Cooperative Manipulation and Motion Planning Under Signal Temporal Logic Specifications


    Beteiligte:
    Sewlia, Mayank (Autor:in)

    Erscheinungsdatum :

    2023-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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