In this paper, we present a new approach to robot motion planning that anticipates the use of visionbased feedback control during task execution. We accomplish this by incorporating an image-basedvisualservo (IBVS) ...
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In this paper, we present a new approach to robot motion planning that anticipates the use of visionbased feedback control during task execution. We accomplish this by incorporating an image-basedvisualservo (IBVS) controller directly into the steering function used by a Rapidly Exploring Random Tree (RRT) planner. Our approach requires a number of extensions to traditional RRT-style planning. First, we derive a new sampling strategy that augments the usual state information by including image features that will be used by the IBVS control law. These augmented samples are then used by our new IBVS steering function, which simulates an IBVS control law to generate local trajectories that extend the current tree. These trajectories must be validated to ensure that they are collision-free and that all image features remain unoccluded and within the camera field of view throughout the local trajectory. We also provide a formal proof showing that the proposed approach is probabilistically complete. We have applied our approach to the problem of planning trajectories for three different systems: a robotic arm, an unmanned aerial vehicle (UAV) and a car-like robot, which are equipped with an IBVS control law. We explore performance trade-offs in the control design via simulation studies and demonstrate real-world effectiveness via experiments in which a small-scale car-like robot uses IBVS to navigate a track that includes a number of obstacles and potential occlusions. By exploring performance trade-offs, we mean that several elements, such as the metric used to identify nearest neighbors in the RRT and the steering method used to generate nodes, are tested and compared. (c) 2023 Elsevier B.V. All rights reserved.
A discontinuous model recovery anti-windup technique is proposed for a double integrator with the output measurement corrupted by a time-varying scaling factor. This challenging measurement configuration arises in vis...
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A discontinuous model recovery anti-windup technique is proposed for a double integrator with the output measurement corrupted by a time-varying scaling factor. This challenging measurement configuration arises in vision-basedcontrol, where the position of an object moving in the three-dimensional space is determined using two-dimensional images. We prove uniform global asymptotic stability of the closed loop by applying an invariance principle argument to the regularized dynamics. The effectiveness of the proposed approach is illustrated on a visual aircraft landing simulation example. (C) 2019 Elsevier Ltd. All rights reserved.
This paper presents a sliding-mode observer-based model predictive control (SMO-MPC) strategy for image-basedvisualservoing (IBVS) of fully-actuated underwater vehicles subject to field of view and actuator constrai...
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This paper presents a sliding-mode observer-based model predictive control (SMO-MPC) strategy for image-basedvisualservoing (IBVS) of fully-actuated underwater vehicles subject to field of view and actuator constraints and model uncertainties. In the proposed SMO-MPC controller, the visual system model and the approximate underwater vehicle model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. With the consideration of system uncertainties, including external disturbances and unknown dynamic parameters, a sliding-mode observer is designed to estimate the modeling mismatch, which is feedforward to the dynamic model in MPC. The actual control signals are generated at each step by minimizing a cost function of predicted trajectories under system constraints. The effectiveness of the proposed SMO-MPC IBVS controller is verified by comparative simulations using a fully-actuated underwater vehicle with different control configurations.
This paper proposes an image-based visual servo control (IBVS) method that integrates the kinematics of both a robotic binocular head and cameras with the dynamics of the binocular head and uses a fuzzy sliding mode c...
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This paper proposes an image-based visual servo control (IBVS) method that integrates the kinematics of both a robotic binocular head and cameras with the dynamics of the binocular head and uses a fuzzy sliding mode control algorithm. The proposed method utilises ultrasonic sensors to supply distance information to the visualservo system. In image processing, an attention window is estimated to mark the 3D moving object: the size of the window can increase or decrease according to the size of the object. Finally, two experiments based on the multiple-sensor binocular head are performed to verify the theoretical results.
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