A hierarchical approach to minimum-time control of industrial robots

Saed Al Homsi 1 Alexander Sherikov 1 Dimitar Dimitrov 1 Pierre-Brice Wieber 1
1 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : A novel approach to minimum-time control is presented. It is stated in terms of a hierarchical optimization problem, which is standard in the field of robotics. This is advantageous as already existing tools can be used to approach its solution. Our formulation is applied to the online generation of trajectories for industrial robots performing pick and place operations in the presence of obstacles. Model predictive control is used in order to achieve reactive system behavior and to obtain accurate local approximations of the collision avoidance constraints (which are nonconvex). Our approach has the capacity to suppress high frequency chattering in the control signal in the presence of noise: a common drawback of aggressive control strategies. Experiment using two SCARA robots that share the same working environment is used to evaluate the presented approach.
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Saed Al Homsi, Alexander Sherikov, Dimitar Dimitrov, Pierre-Brice Wieber. A hierarchical approach to minimum-time control of industrial robots. ICRA 2016 - IEEE International Conference on Robotics and Automation, May 2016, Stockholm, Sweden. pp.2368-2374, ⟨10.1109/ICRA.2016.7487386⟩. ⟨hal-01418396⟩

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