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Epsilon-Optimal Synthesis for Vehicles With Vertically Bounded Field-Of-View

IEEE TRANSACTIONS ON AUTOMATIC control 2015年第5期60卷 1204-1218页

作者： Salaris, Paolo Cristofaro, Andrea Pallottino, Lucia Bicchi, Antonio Univ Pisa Res Ctr Enrico Piaggio Pisa Italy Univ Pisa Dipartimento Ingn Informaz Pisa Italy Univ Camerino Sch Sci & Technol I-62032 Camerino Italy Ist Italiano Tecnol Dept Adv Robot Genoa Italy

This paper presents a contribution to the problem of obtaining an optimal synthesis for shortest paths for a unicycle guided by an on-board limited Field-Of-View (FOV) sensor, which must keep a given landmark in sight. Previous works on this subject have provided an optimal synthesis for the case in which the FOV is limited in the horizontal directions (H-FOV, i.e., left and right boundaries). In this paper we study the complementary case in which the FOV is limited only in the vertical direction (V-FOV, i.e., upper and lower boundaries). With respect to the H-FOV case, the vertical limitation is all but a simple extension. Indeed, not only the geometry of extremal arcs is different, but also a more complex structure of the synthesis is revealed by analysis. We will indeed show that there exist initial configurations for which the optimal path does not exist. In such cases, we provide an epsilon-optimal path whose length approximates arbitrarily well any other shorter path. Finally, we provide a partition of the motion plane in regions such that the optimal or epsilon-optimal path from each point in that region is univocally determined.

关键词： Autonomous robots optimal control path planning synthesis visual servo control

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An End-to-End Learning-Based control Signal Prediction for Autonomous Robotic Colonoscopy

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IEEE ACCESS 2024年 12卷 1280-1290页

作者： Nguyen, Van Sy Hwang, Bohyun Kim, Byungkyu Jung, Jay Hoon Korea Aerosp Univ Dept Aerosp & Mech Engn Goyang 10540 South Korea Univ Cent Florida Mech & Aerosp Engn Dept Orlando FL 32816 USA Korea Aerosp Univ Sch Aerosp & Mech Engn Goyang 10540 South Korea Korea Aerosp Univ Sch Artificial Intelligence Goyang 10540 South Korea

We introduce a novel 3 degrees-of-freedom based robotic colonoscopy system that performs the necessary movements for colonoscopy while working within the movement range of a flexible colonoscope (FC). In addition, we have developed deep learning models to generate motor control signals directly from input images without the need for motor control signal labels. The first presented model comprises a deep learning algorithm for predicting steering points and an image-based visual servo control (IBVS) algorithm for generating the motor control signal. The experiments showed that the proposed model's cecal intubation time (CIT) and rate (CIR) are comparable to those of human operators, despite requiring a shorter training time. Furthermore, we propose a model that replaces the IBVS algorithm with a deep learning algorithm that does not rely on rotation angles. The second model showed similar CIT (165s) and CIR (92%) compared to the first model. Finally, the last model, which solely comprises a single deep learning algorithm, demonstrates a reduction in CIT (127s) and an increase in CIR (96%), resulting in reduced physical demand for operators, improved safety, and shorter patient recovery time.

关键词： Autonomous system deep learning robotic colonoscopy visual servo control

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Accelerated Dual Neural Network controller for visual servoing of Flexible Endoscopic Robot With Tracking Error, Joint Motion, and RCM Constraints

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2022年第9期69卷 9246-9257页

作者： Cui, Zhiwei Li, Weibing Zhang, Xue Chiu, Philip Wai Yan Li, Zheng Chinese Univ Hong Kong Multiscale Med Robot Ctr Hong Kong Peoples R China Chinese Univ Hong Kong Chow Yuk Ho Technol Ctr Innovat Med Hong Kong Peoples R China Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Chinese Univ Hong Kong Dept Surg Hong Kong Peoples R China Chinese Univ Hong Kong Li Ka Shing Inst Hlth Sci Hong Kong Peoples R China

Aiming at the requirements for endoscope in minimally invasive surgery, a dual neural network (DNN) controller is designed for a flexible endoscopic robot (FER) with 10 DOF. First, the FER's kinematics model with remote center of motion (RCM) constraints is established. Then, a quadratic programming control scheme involving the tracking error, joint motion, and RCM constraints of the FER is proposed. A DNN solver of the control scheme, which is activated by the sum of linear and sign-bi-power activation function with adjustable parameters (LSB-AF-AP), is designed, and its convergence rate (CR) and antinoise ability can be improved via adjusting the parameters of LSB-AF-AP. The DNN can converge rapidly in finite time and it is proved by utilizing the Lyapunov theory. Compared with the previous linear AFs applied to the DNN, theoretical analysis indicates that the DNN activated by the LSB-AF-AP has an accelerated CR. Meanwhile, it is proved that the solution obtained by using the designed DNN is the optimal solution of the control scheme. Finally, simulations using the ROS and Gazebo, and an experiment performed on a real FER are conducted. The simulative and experimental results verify that the control scheme can complete the target tracking task well, and the CR and antinoise ability of the algorithm can be further improved via adjusting the parameters of LSB-AF-AP.

关键词： Robots Surgery Robot kinematics Endoscopes Service robots Kinematics visualization Dual neural network (DNN) flexible endoscopic robot (FER) remote center of motion (RCM) visual servo control

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Addressing corner detection issues for machine vision based UAV aerial refueling

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MACHINE VISION AND APPLICATIONS 2007年第5期18卷 261-273页

作者： Vendra, Soujanya Campa, Giampiero Napolitano, Marcello R. Mammarella, Marco Fravolini, Mario L. Perhinschi, Mario G. W Virginia Univ Dept Aerosp Engn Morgantown WV 26506 USA Univ Perugia Dept Elect & Informat Engn I-06100 Perugia Italy

This paper describes the results of the analysis of specific 'corner detection' algorithms within a Machine Vision approach for the problem of aerial refueling for unmanned aerial vehicles. Specifically, the performances of the SUSAN and the Harris corner detection algorithms have been compared. A critical goal of this study was to evaluate the interface of these feature extraction schemes with the successive detection and labeling, and pose estimation schemes in the overall scheme. Closed-loop simulations were performed using a Simulink (R)-based simulation environment to reproduce docking maneuvers using the US Air Force refueling boom.

关键词： corner detection labeling pose estimation visual servo control

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Adaptive velocity control for UAV boat landing: A neural network and particle swarm optimization approach

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2024年第1期111卷 1-18页

作者： Wu, Li-Fan Wang, Zihan Rastgaar, Mo Mahmoudian, Nina Purdue Univ W Lafayette IN 47906 USA

Achieving precise landing of Unmanned Aerial Vehicles (UAVs) onto moving platforms, such as Autonomous Surface Vehicles (ASVs), is challenging, particularly in GPS-denied environments with dynamic disturbances. Conventional methods often rely on high-level waypoint navigation, extensive manual tuning, and expensive sensors. In this work, we propose an adaptive Proportional-Integral-Derivative (PID) controller optimization using a Neural Network-Particle Swarm Optimization (NN-PSO) algorithm. The algorithm dynamically tunes the PID controller, significantly reducing manual tuning effort, while relying solely on a low-cost camera and altitude sensor. The NN-PSO algorithm allows the UAV to land with an average error of 5 cm on static platforms and 10 cm on moving boats, based on multiple test flights. Our method also increases the maximum landing speed to 80.9% of the UAV's top flight speed, a considerable improvement over existing systems. Our approach not only optimizes landing precision but also introduces techniques for ensuring soft landings, reducing oscillations, and preventing target misses. These enhancements make the method robust across varying flight altitudes and ASV speeds. Furthermore, this approach is applicable to a variety of GPS-denied scenarios, including rescue missions, package deliveries, and workspace inspections, without requiring costly equipment or extensive parameter tuning. Field experiments confirm the precision and stability of the proposed system, validating its performance in real-world conditions. [Video]

关键词： Adaptive control Autonomous systems visual servo control Sensor fusion visual servoing Unmanned aerial vehicles

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Globally exponentially stable observer for vision-based range estimation

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MECHATRONICS 2012年第4期22卷 381-389页

作者： Dani, A. P. Fischer, N. R. Kan, Z. Dixon, W. E. Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA

A reduced-order nonlinear observer is developed to estimate the distance from a moving camera to a feature point on a static object (i.e., range identification), where full velocity and linear acceleration feedback of the calibrated camera is provided. The contribution of this work is to develop a global exponential range observer which can be used for a larger set of camera motions than existing observers. The observer is shown to be robust against external disturbances in the sense that the observer is (sic)(p)for all p is an element of [1, infinity] stable even if the target object is moving or the camera motion is perturbed. The presented observer identifies the range provided an observability condition commonly used in literature is satisfied and is shown to be exponentially stable even if camera motion satisfies a less restrictive observability condition. A sufficient condition on the observer gain is derived to prove stability using a Lyapunov-based analysis. Experimental results are provided to show robust performance of the observer using an autonomous underwater vehicle (AUV). (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Structure from motion Nonlinear observers visual servo control Vision-based loccalization

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Vision-based control of robotic manipulator for citrus harvesting

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2014年 102卷 146-158页

作者： Mehta, S. S. Burks, T. F. Univ Florida Dept Ind & Syst Engn Res & Engn Educ Facil Shalimar FL 32579 USA Univ Florida Dept Agr & Biol Engn Gainesville FL 32611 USA

The main contribution of this paper is in the development of vision-based estimation and control system for robotic fruit harvesting and rigorous stability analysis to guarantee performance of the closed-loop system. The presented cooperative visual servo controller benefits from the large field-of-view of a fixed camera and the accuracy of a camera-in-hand (CiH). Computationally inexpensive perspective transformation-based range estimation method obtains 3D fruit position using a monocular camera to enable real-time manipulator control. A rotation controller is developed to orient the robot such that the target fruit selected by the fixed camera can be viewed by the CiH attached to the end-effector. Subsequently, the end-effector can be servoed to the target fruit location using the presented pursuit guidance based hybrid translation controller. Lyapunov-based stability analysis guarantees global exponential regulation of the end-effector. Numerical simulations verify the feasibility of the developed controller while the performance is evaluated on a seven degrees-of-freedom kinematically redundant manipulator using an artificial citrus tree. The position of the fruit was randomly selected, and the closed-loop visual servo control experiment was performed 21 times to analyze the repeatability and accuracy of the developed controller. With 95% confidence level the expected position of the robot end-effector is observed to lie within the confidence ellipsoid. The accuracy of the controller was observed to be about 15 mm, thus making the system suitable for harvesting medium and large varieties of citrus fruit but may limit operation for small varieties such as page and blood oranges. (C) 2014 Elsevier B.V. All rights reserved.

关键词： visual servo control Robotic harvesting Agricultural robotics

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Automated Four-Point Probe Measurement of Nanowires Inside a Scanning Electron Microscope

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IEEE TRANSACTIONS ON NANOTECHNOLOGY 2011年第4期10卷 674-681页

作者： Ru, Changhai Zhang, Yong Sun, Yu Zhong, Yu Sun, Xueliang Hoyle, David Cotton, Ian Soochow Univ Robot & Microsyst Ctr Suzhou 215021 Peoples R China Univ Toronto Adv Micro & Nanosyst Lab Toronto ON M5S 3G8 Canada Univ Western Ontario Dept Mech & Mat Engn London ON N6A 5B9 Canada Hitachi High Technol Canada Inc Toronto ON M9W 6A4 Canada

Nanomanipulation inside a scanning electron microscope (SEM) has been employed to maneuver and characterize nanomaterials. Despite recent efforts toward automated nanomanipulation, it is still largely conducted manually. In this paper, we demonstrate automated nanomanipulation inside an SEM for a well-structured nanomanipulation task via visual servo control and a vision-based contact-detection method using SEM as a vision sensor. Four-point probe measurement of individual nanowires is achieved automatically by controlling four nanomanipulators with SEM visual feedback. A feedforward controller is incorporated into the control system to improve response time. This technique represents an advance in nanomanipulation inside SEM and can be extended to other nanomanipulation tasks.

关键词： Automated nanomanipulation contact detection four-point probe visual servo control

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Multirotor nonlinear model predictive control based on visual servoing of evolving features

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AUTONOMOUS ROBOTS 2024年第8期48卷 1-22页

作者： Aspragkathos, Sotirios N. Rousseas, Panagiotis Karras, George C. Kyriakopoulos, Kostas J. Natl Tech Univ Athens NTUA Sch Mech Engn Control Syst Lab CSL 9 Heroon Polytech StrZografou Athens 15780 Greece Univ Thessaly Dept Informat & Telecommun 3rd Km Old Natl Rd LamiaLamia Athens 35100 Greece NYU Engn Div Abu Dhabi 128188 U Arab Emirates NYU Ctr AI & Robot CAIR Abu Dhabi 128188 U Arab Emirates

This article presents a visual servoing Nonlinear Model Predictive control (NMPC) scheme for autonomously tracking a moving target using multirotor Unmanned Aerial Vehicles (UAVs). The scheme is developed for surveillance and tracking of contour-based areas with evolving features. NMPC is used to manage input and state constraints, while additional barrier functions are incorporated in order to ensure system safety and optimal performance. The proposed control scheme is designed based on the extraction and implementation of the full dynamic model of the features describing the target and the state variables. Real-time simulations and experiments using a quadrotor UAV equipped with a camera demonstrate the effectiveness of the proposed strategy.

关键词： visual servo control Predictive control for nonlinear systems Multi-rotors control Autonomous robots

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Predictive visual control network for occlusion solution in human-following robot

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ASSEMBLY AUTOMATION 2021年第2期41卷 187-199页

作者： Zou, Juncheng Univ Sci & Technol Beijing Beijing Peoples R China

Purpose The purpose of this paper is to propose a new video prediction-based methodology to solve the manufactural occlusion problem, which causes the loss of input images and uncertain controller parameters for the robot visual servo control. Design/methodology/approach This paper has put forward a method that can simultaneously generate images and controller parameter increments. Then, this paper also introduced target segmentation and designed a new comprehensive loss. Finally, this paper combines offline training to generate images and online training to generate controller parameter increments. Findings The data set experiments to prove that this method is better than the other four methods, and it can better restore the occluded situation of the human body in six manufactural scenarios. The simulation experiment proves that it can simultaneously generate image and controller parameter variations to improve the position accuracy of tracking under occlusions in manufacture. Originality/value The proposed method can effectively solve the occlusion problem in visual servo control.

关键词： Deep neural networks Occlusion solution Video prediction visual servo control

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