Conjugated Visual Predictive Control for Constrained Visual Servoing

Fallah, Mostafa M. H.; Janabi–Sharifi, Farrokh

doi:10.1007/s10846-020-01299-6

Cited by 7 publications

(2 citation statements)

References 30 publications

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“…In other words, images taken by the camera provide feedback to the servo motion control of the robot. In terms of control architecture and error function definitions, VS methods can be classified as (1) Image-Based Visual Servoing (IBVS), (2) Position-Based Visual Servoing (PBVS), and (3) Hybrid Visual Servoing (HVS) [1,2]. The PBVS methods provide robot trajectory paths that are feasible in a 3D space.…”

Section: Introductionmentioning

confidence: 99%

A Cascaded and Adaptive Visual Predictive Control Approach for Real-Time Dynamic Visual Servoing

Sajjadi

Mehrandezh

Janabi–Sharifi

2022

Drones

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In the past two decades, Unmanned Aerial Vehicles (UAVs) have gained attention in applications such as industrial inspection, search and rescue, mapping, and environment monitoring. However, the autonomous navigation capability of UAVs is aggravated in GPS-deprived areas such as indoors. As a result, vision-based control and guidance methods are sought. In this paper, a vision-based target-tracking problem is formulated in the form of a cascaded adaptive nonlinear Model Predictive Control (MPC) strategy. The proposed algorithm takes the kinematics/dynamics of the system, as well as physical and image constraints into consideration. An Extended Kalman Filter (EKF) is designed to estimate uncertain and/or time-varying parameters of the model. The control space is first divided into low and high levels, and then, they are parameterised via orthonormal basis network functions, which makes the optimisation- based control scheme computationally less expensive, therefore suitable for real-time implementation. A 2-DoF model helicopter, with a coupled nonlinear pitch/yaw dynamics, equipped with a front-looking monocular camera, was utilised for hypothesis testing and evaluation via experiments. Simulated and experimental results show that the proposed method allows the model helicopter to servo toward the target efficiently in real-time while taking kinematic and dynamic constraints into account. The simulation and experimental results are in good agreement and promising.

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Section: Introductionmentioning

confidence: 99%

A Cascaded and Adaptive Visual Predictive Control Approach for Real-Time Dynamic Visual Servoing

Sajjadi

Mehrandezh

Janabi–Sharifi

2022

Drones

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“…Li et al [13] proposed a hierarchical visual MPC scheme where the kinematic layer was used to plan the steering speed of WMRs and the dynamic layer is to track the planned steering speed. Mostafa and Farrofh [14] presented a conjugate vision MPC method to generate optimal trajectory, and in Cao et al [15], a two-stage visual stabilization controller consisting of kinematics and dynamics ones was designed using nonlinear MPC. Further, Ke et al [16] presented an image-based MPC strategy to stabilize a WMR with physical constraints, and Hajiloo et al [17] designed a visual servoing robust MPC algorithm to satisfy physical limitations and visibility constraints.…”

Section: Introductionmentioning

confidence: 99%

Quasi‐min‐max MPC for visual servoing stabilization of omnidirectional wheeled mobile robots

Lin

Xing

et al. 2022

Asian Journal of Control

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This paper proposes a new visual servoing quasi‐min‐max MPC algorithm for stabilization control of an omnidirectional wheeled mobile robot subject to physical and visual constraints. The visual servoing dynamics of the robot are modeled as the state‐dependent linear error system with nonlinear control inputs of rotation and deflection velocities of wheels. The state‐dependent linear error system is covered as linear parameters‐varying models which is used to design the visual servoing quasi‐min‐max MPC controller. The actual control inputs of the robot are then computed by the solution of an inverse algebraic equation of the MPC actions. The recursive feasibility and stability of the new visual servoing MPC are ensured by some LMIs conditions. The performance and practicability of the visual servoing MPC are verified by some simulation and experiment results.

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