Motion planning is central to the efficient operation and autonomy of robots in the industry. Generally, motion planning of industrial robots is treated in a two-step approach. First, a geometric path between the start and goal position is planned where the objective is to achieve as short path as possible together with avoiding obstacles. Alternatively, a pre-defined geometric path is provided by the end user. Second, the velocity profile along the geometric path is calculated accounting for system dynamics together with other constraints. This approach is computationally efficient, but yield sub-optimal solutions as the system dynamics is not considered in the first step when the geometric path is planned. In this thesis, an alternative to the two-step approach is investigated and a trajectory planner is designed and implemented which plans both the geometric path and the velocity profile simultaneously. The motion planning problem is formulated as an optimal control problem, which is solved by a direct collocation method where the trajectory is parametrised by splines, and the spline nodes and knots are used as optimization variables. The implemented trajectory planner is evaluated in simulations, where the planner is applied to a simple planar elbow robot and ABB's SCARA robot IRB 910SC. Trade-off between computation time and optimality is identified and the results indicate that the trajectory planner yields satisfactory solutions. On the other hand, the simulations indicate that it is not possible to apply the proposed method on a real robot in real-time applications without significant modifications in the implementation to decrease the computation time.


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    Title :

    Sensor-Based Trajectory Planning in Dynamic Environments


    Contributors:

    Publication date :

    2018-01-01


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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