Robot Online Task and Trajectory Planning using Mixed-Integer Model Predictive Control

A monolithic integration of the robot online task allocation and trajectory planning within the framework of a hybrid model predictive controller is introduced. To this end, the underlying mixed-integer nonlinear programming (MINLP) problem is transformed into a relaxed mixed-integer quadratically c...

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Vydané v:2022 European Control Conference (ECC) s. 2005 - 2011
Hlavní autori: Tika, Argtim, Gashi, Fatos, Bajcinca, Naim
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: EUCA 12.07.2022
Predmet:
Manipulators
Programming
Real-time systems
Robot kinematics
Software
Software algorithms
Trajectory planning
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Shrnutí:A monolithic integration of the robot online task allocation and trajectory planning within the framework of a hybrid model predictive controller is introduced. To this end, the underlying mixed-integer nonlinear programming (MINLP) problem is transformed into a relaxed mixed-integer quadratically constrained programming (MIQCP) problem, suitable to generate feasible robot trajectories online. The proposed algorithm is implemented and validated on an experimental setup using the robot operating system (ROS) software and a robot arm performing discrete pick-and-place tasks.
DOI:10.23919/ECC55457.2022.9838243