Vision system for mobile robots for tracking moving targets, based on robot motion and stereo vision information

Kim, Tae Il; Bahn, Wook; Lee, Chang-Hun; Lee, Tae-jae; Shaikh, Muhammad Muneeb; Kim, Kwangsoo

doi:10.1109/sii.2011.6147522

Cited by 10 publications

(7 citation statements)

References 2 publications

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“…Stereo vision uses similar principles that humans and animals utilize to perceive depth information using binocular vision. In the field of Robotics, stereo vision is deployed for applications which require depth perception (e.g robot navigations) [20].…”

Section: F Stereo Visionmentioning

confidence: 99%

Anomaly inspection in sewer pipes using stereo vision

Huynh

Ross

Martchenko

et al. 2015

2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

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This paper describes and evaluates a new sensing methodology for anomaly inspection in sewer pipes using a machine vision approach. Currently, most commercial pipe inspection systems include a mobile remote platform and one or more Closed Circuit Television (CCTV) cameras. These inspection systems are slow, costly and have limited accuracy (caused by humans or environmental reasons). More sophisticated approaches (Laser-based, Infra-red Thermography, Ultrasonicbased and Ground Penetrating Radar) suffer from, lack of resolution and an inability to detect water inflow. The main objective of this research is to apply stereo vision technique to generate 3D images of anomalies in sewer pipes in order to achieve high efficiency and accuracy for pipe inspection. The results showed that various types of defects were successfully reconstructed for later advanced processing.

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Section: F Stereo Visionmentioning

confidence: 99%

Anomaly inspection in sewer pipes using stereo vision

Huynh

Ross

Martchenko

et al. 2015

2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

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“…These multiagent robotic and sensor systems have a number of advantages over single agent systems, including robustness to failures of individual agents, ease of reconfiguration, and the ability to perform challenging tasks such as environmental monitoring [3][4][5], target tracking [6][7][8][9], source seeking [10,11], cooperative wireless airborne communication [12], that an individual agent would not be capable of performing. These advantages have paved way for the design of novel algorithms that allow the agents to overcome the problems of formation control, coordinated path following, target tracking and source seeking [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Gradient-free numerical optimization-based extremum seeking control for multiagent systems

Vweza

Chong

Lee

2015

Int. J. Control Autom. Syst.

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In this article, we develop a model-and gradient-free numerical optimization-based extremum seeking control scheme to solve the problem of formation control and target tracking in multiagent systems. Unlike in conventional gradient-based extremum seeking control, we do not make the strong assumption that the gradient and/or the Hessian of the objective function can be analytically computed from continuously measured system states. Rather, we employ a derivative-free numerical optimization method that directly builds an approximate model of the objective function. After showing the global convergence of the optimization algorithm, we use a regulator to drive the states of the system to the optimizer of the unknown performance function. We demonstrate the performance of the control scheme by simulations where we control three agents that are given a random initial position and are required to maintain an equilateral triangle formation while tracking and localizing a source signal with unknown spatial dynamics.

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“…Most of all use one [3,6] or two cameras to track moving targets. With stereo visual servoing system [7,8,13] the posture of the target can be determined in 3D Cartesian coordinates. From control methods point of view one can classify the visual servoing systems into kinematic [8] and dynamic controls.…”

Section: Introductionmentioning

confidence: 99%

“…From control methods point of view one can classify the visual servoing systems into kinematic [8] and dynamic controls. With the kinematics control method, the controllers of the systems have to calculate the necessary speeds of robot joints so that the tracking errors must reach 0 [1,7,10]. But, the most important condition is that the joints of robot can be controlled exactly at any desired speed.…”

Section: Introductionmentioning

confidence: 99%

A new control method for stereo visual servoing system with Pan-tilt platform

Chung¹,

Cát²

2015

JCC

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This paper proposes a new control method for Pan-Tilt stereo camera system to track a moving object when there are many uncertainties in the parameters of both camera and Pan-Tilt platform. If a pair of cameras placed on the Pan-Tilt robot, it is unnecessary for its installation location to be determined accurately. Assuming that the optical parameters like focal length of two cameras in the simulation are the same. A two degree of freedom Pan-Tilt platform holding camera has many uncertain parameters such as inertial moment, Jacobian matrix, the friction and noise impact, etc. The proposed control algorithm is highly adaptive and robust due to the use of a compensating neural network with on-line learning rule. The asymptotic stability of overall control system is proved by Lyapunov's stability method.

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Vision system for mobile robots for tracking moving targets, based on robot motion and stereo vision information

Cited by 10 publications

References 2 publications

Anomaly inspection in sewer pipes using stereo vision

Anomaly inspection in sewer pipes using stereo vision

Gradient-free numerical optimization-based extremum seeking control for multiagent systems

A new control method for stereo visual servoing system with Pan-tilt platform

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