Citation

BibTex format

@article{AlAttar:2022:10.3389/frobt.2022.809114,
author = {AlAttar, A and Chappell, D and Kormushev, P},
doi = {10.3389/frobt.2022.809114},
journal = {Frontiers in Robotics and AI},
pages = {1--9},
title = {Kinematic-model-free predictive control for robotic manipulator target reaching with obstacle avoidance},
url = {http://dx.doi.org/10.3389/frobt.2022.809114},
volume = {9},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Model predictive control is a widely used optimal control method for robot path planning andobstacle avoidance. This control method, however, requires a system model to optimize controlover a finite time horizon and possible trajectories. Certain types of robots, such as softrobots, continuum robots, and transforming robots, can be challenging to model, especiallyin unstructured or unknown environments. Kinematic-model-free control can overcome thesechallenges by learning local linear models online. This paper presents a novel perception-basedrobot motion controller, the kinematic-model-free predictive controller, that is capable of controllingrobot manipulators without any prior knowledge of the robot’s kinematic structure and dynamicparameters and is able to perform end-effector obstacle avoidance. Simulations and physicalexperiments were conducted to demonstrate the ability and adaptability of the controller toperform simultaneous target reaching and obstacle avoidance.
AU - AlAttar,A
AU - Chappell,D
AU - Kormushev,P
DO - 10.3389/frobt.2022.809114
EP - 9
PY - 2022///
SN - 2296-9144
SP - 1
TI - Kinematic-model-free predictive control for robotic manipulator target reaching with obstacle avoidance
T2 - Frontiers in Robotics and AI
UR - http://dx.doi.org/10.3389/frobt.2022.809114
UR - https://www.frontiersin.org/articles/10.3389/frobt.2022.809114/full
UR - http://hdl.handle.net/10044/1/93804
VL - 9
ER -

Contact us

Artificial Intelligence Network
South Kensington Campus
Imperial College London
SW7 2AZ

To reach the elected speaker of the network, Dr Rossella Arcucci, please contact:

ai-speaker@imperial.ac.uk

To reach the network manager, Diana O'Malley - including to join the network - please contact:

ai-net-manager@imperial.ac.uk