Mobile Robot Learning from Human Demonstrations with Nonlinear Model Predictive Control

Hu, Yidan; Chen, Guang; Ning, Xiangyu; Dong, Jinhu; Liu, Shu; Knoll, Alois

doi:10.1109/iros40897.2019.8968277

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…Jin et al [11] proposed to use neural networks to combine the T1 and the T3. In our previous works [12], [17], we utilized the hierarchical operational space formulation [18] to combine the three tasks T1, T2, and T3.…”

Section: Related Workmentioning

confidence: 99%

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Hierarchical optimization Control of Redundant Manipulator for Robot-assisted Minimally Invasive Surgery

Chen

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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For the time varying optimization problem, the tracking error cannot converge to zero at the finite time because of the optimal solution changing over time. This paper proposes a novel varying parameter recurrent neural network (VPRNN) based hierarchical optimization of a 7-DoF surgical manipulator for Robot-Assisted Minimally Invasive Surgery (RAMIS), which guarantees task tracking, Remote Center of Motion (RCM) and manipulability index optimization. A theoretically grounded hierarchical optimization framework based is introduced to control multiple tasks based on their priority. Finally, the effectiveness of the proposed control strategy is demonstrated with both simulation and experimental results. The results show that the proposed VPRNN-based method can optimal three tasks at the same time and have better performance than previous work.

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Section: Related Workmentioning

confidence: 99%

“…where d i = vec T J T h T i . Moreover, the new symbol ' ' is defined to simplify the expression in (17),…”

Section: B Problem Formulationmentioning

confidence: 99%

Hierarchical optimization Control of Redundant Manipulator for Robot-assisted Minimally Invasive Surgery

Chen

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…have been designed for vehicle control. Because MPC has the ability to incorporate soft and hard constraints into the online optimizations in a multivariable control framework, it is widely applied in vehicle control field (Hu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties, External Disturbances, and Time-Varying Delay

2021

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In this paper, we design a robust model predictive control (MPC) controller for vehicle subjected to bounded model uncertainties, norm-bounded external disturbances and bounded time-varying delay. A Lyapunov-Razumikhin function (LRF) is adopted to ensure that the vehicle system state enters in a robust positively invariant (RPI) set under the control law. A quadratic cost function is selected as the stage cost function, which yields the upper bound of the infinite horizon cost function. A Lyapunov-Krasovskii function (LKF) candidate related to time-varying delay is designed to obtain the upper bound of the infinite horizon cost function and minimize it at each step by using matrix inequalities technology. Then the robust MPC state feedback control law is obtained at each step. Simulation results show that the proposed vehicle dynamic controller can steer vehicle states into a very small region near the reference tracking signal even in the presence of external disturbances, model uncertainties and time-varying delay. The source code can be downloaded on https://github.com/wenjunliu999.

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“…Puri elaborated on some of the drones available in the market that can be used for agricultural monitoring and observation to get better crop quality and to prevent various forms of damage to the fields (Puri et al, 2017). Currently, most human-robot skill systems focus on the service robot (Hu et al, 2019), manufacturing (Cai et al, 2020), medical rehabilitation (Su et al, 2020c) and robotic teleoperation (Yang et al, 2018c). The research of the humanrobot skill transfer system in agriculture still is one of the most challenging (Yingbai et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Human-robot skills transfer interface for UAV-based precision pesticide in dynamic environments

Zhou

Chen

et al. 2021

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Purpose Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle (UAV) is deployed as a major part of integrated pest management in a precision agriculture system for accurately and cost-effectively distributing pesticides to resist crop diseases and insect pests. Design/methodology/approach With multimodal sensor fusion applying adaptive cubature Kalman filter, the position and velocity are enhanced for the correction and accuracy. A dynamic movement primitive is combined with the Gaussian mixture model to obtain numerous trajectories through the teaching of a demonstration. Further, to enhance the trajectory tracking accuracy under an uncertain environment of the spraying, a novel model reference adaptive sliding mode control approach is proposed for motion control. Findings Experimental studies have been carried out to test the ability of the proposed interface for the pesticides in the crop fields. The effectiveness of the proposed interface has been demonstrated by the experimental results. Originality/value To solve the path planning problem of a complex unstructured environment, a human-robot skills transfer interface is introduced for the UAV that is instructed to follow a trajectory demonstrated by a human teacher.

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Mobile Robot Learning from Human Demonstrations with Nonlinear Model Predictive Control

Cited by 10 publications

References 18 publications

Hierarchical optimization Control of Redundant Manipulator for Robot-assisted Minimally Invasive Surgery

Hierarchical optimization Control of Redundant Manipulator for Robot-assisted Minimally Invasive Surgery

Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties, External Disturbances, and Time-Varying Delay

Human-robot skills transfer interface for UAV-based precision pesticide in dynamic environments

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