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Article

Kinematic-Model-Free Redundancy Resolution Using Multi-Point Tracking and Control for Robot Manipulation

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Robot Intelligence Lab, Dyson School of Design Engineering, Imperial College London, Exhibition Road, London SW7 2DB, UK
2
Dubai Future Lab, 77 Sheikh Zayed Road, Dubai, United Arab Emirates
3
Hamlyn Centre, Imperial College London, Exhibition Road, London SW7 2BU, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Dario Richiedei
Appl. Sci. 2021, 11(11), 4746; https://doi.org/10.3390/app11114746
Received: 1 May 2021 / Revised: 20 May 2021 / Accepted: 20 May 2021 / Published: 21 May 2021
Robots have been predominantly controlled using conventional control methods that require prior knowledge of the robots’ kinematic and dynamic models. These controllers can be challenging to tune and cannot directly adapt to changes in kinematic structure or dynamic properties. On the other hand, model-learning controllers can overcome such challenges. Our recently proposed model-learning orientation controller has shown promising ability to simultaneously control a three-degrees-of-freedom robot manipulator’s end-effector pose. However, this controller does not perform optimally with robots of higher degrees-of-freedom nor does it resolve redundancies. The research presented in this paper extends the state-of-the-art kinematic-model-free controller to perform pose control of hyper-redundant robot manipulators and resolve redundancies by tracking and controlling multiple points along the robot’s serial chain. The results show that with more control points, the controller is able to reach desired poses in fewer steps, yielding an improvement of up to 66%, and capable of achieving complex configurations. The algorithm was validated by running the simulation 100 times, and it was found that, in 82% of the times, the robot successfully reached the desired target pose within 150 steps. View Full-Text
Keywords: kinematic-model-free control; model-learning control; redundancy resolution; multi-point tracking; adaptive control kinematic-model-free control; model-learning control; redundancy resolution; multi-point tracking; adaptive control
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MDPI and ACS Style

AlAttar, A.; Cursi, F.; Kormushev, P. Kinematic-Model-Free Redundancy Resolution Using Multi-Point Tracking and Control for Robot Manipulation. Appl. Sci. 2021, 11, 4746. https://doi.org/10.3390/app11114746

AMA Style

AlAttar A, Cursi F, Kormushev P. Kinematic-Model-Free Redundancy Resolution Using Multi-Point Tracking and Control for Robot Manipulation. Applied Sciences. 2021; 11(11):4746. https://doi.org/10.3390/app11114746

Chicago/Turabian Style

AlAttar, Ahmad, Francesco Cursi, and Petar Kormushev. 2021. "Kinematic-Model-Free Redundancy Resolution Using Multi-Point Tracking and Control for Robot Manipulation" Applied Sciences 11, no. 11: 4746. https://doi.org/10.3390/app11114746

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