Visual control through the trifocal tensor for nonholonomic robots

López‐Nicolás, Gonzalo; Guerrero, J. J.; Sagüés, Carlos

doi:10.1016/j.robot.2009.09.005

Cited by 42 publications

(34 citation statements)

References 31 publications

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“…[6], a switching control scheme based on the epipolar geometry and homography was proposed, which took advantage of both models avoiding the drawbacks of each one and allowing a smooth motion of robot. Another feasible way to overcome the drawbacks of these two geometric constraints is to use trifocal tensor, 7,8 which Vision-based pose stabilization of an uncertain mobile robot describes the relative geometry of three views completely and is independent of the observed scene. Recently, Zhang et al 9 proposed a hybrid vision-based stabilization strategy based on a motionestimation technique, which can be applied in both planar and non-planar scenes and required no matrix estimation or decomposition.…”

Section: Introductionmentioning

confidence: 99%

Adaptive dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot

Cao

Yin

et al. 2014

Robotica

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dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot . Robotica, SUMMARYThis paper investigates the vision-based pose stabilization of an electrically driven nonholonomic mobile robot with parametric uncertainties in robot kinematics, robot dynamics, and actuator dynamics. A robust adaptive visual stabilizing controller is proposed with the utilization of adaptive control, backstepping, and dynamic surface control techniques. For the controller design, the idea of backstepping is used and the adaptive control approach is adopted to deal with all uncertainties. We also apply the dynamic surface control method to avoid the repeated differentiations of virtual controllers existing in the backstepping design procedure such that the control development is easier to be implemented. Moreover, to attenuate the effect of disturbances on control performance, smooth robust compensators are exploited. It is proved that all signals in the closed-loop system can be guaranteed to be uniformly ultimately bounded. Finally, simulation results are presented to illustrate the performance of the proposed controller.

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Section: Introductionmentioning

confidence: 99%

Adaptive dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot

Cao

Yin

et al. 2014

Robotica

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“…Although the trifocal tensor (TT) is more general, more robust, and without the drawbacks of other geometric constraints [6], it has been less exploited in visual control. The 2-D TT has been introduced for visual control of mobile robots using an overconstrained controller, which may suffer from local minima problems [7]. This is overcome in [8] by defining a square control system and by using direct feedback of the elements of the 1-D TT in a two-step switching control law.…”

Section: Introductionmentioning

confidence: 99%

Exploiting the Trifocal Tensor in Dynamic Pose Estimation for Visual Control

Becerra

Sagüés

2013

IEEE Trans. Contr. Syst. Technol.

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Image-based approaches for visual control are memoryless, and they depend on the information extracted from the image plane. We propose the use of dynamic pose estimation in the task of driving a mobile robot to a desired location specified by a target image. This approach reduces the dependence of the control on the quality of current visual data and facilitates the planning of complex tasks. The pose estimation exploits the 1-D trifocal tensor (TT) as measurement, which allows us to obtain a semicalibrated estimation scheme that is valid for any visual sensor obeying a central projection model. The contribution of this brief is a novel observability analysis of the estimation problem from the 1-D TT using nonlinear tools, as well as the demonstration of the validity of closed-loop control from the estimated pose by showing a separation principle in our nonlinear framework. The overall position-based scheme drives the robot to a desired pose through smooth velocities without the need of a target model, either scene reconstruction or depth information. The effectiveness of the approach is evaluated via real-world experiments.

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“…3 Basri et al 31 is an early example of the use of a two-view model expressed by the epipolar geometry for control purposes. Nonholonomic visual control methods have been proposed using this model 32 and the trifocal tensor, 33,34 which encapsulates the geometric constraints between three views 30 and provides improved robustness. Shademan and Jägersand 35 introduced the use of the 2D trifocal tensor to control a 6-Degree of Freedom (DOF) manipulator.…”

Section: Introductionmentioning

confidence: 99%

Sinusoidal input-based visual control for nonholonomic vehicles

2013

Self Cite

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This paper proposes a new visual control approach based on sinusoidal inputs to be used on a nonholonomic robot. We present several contributions: In our method, developed considering a unicycle kinematic model, sinusoids are used in such a way that the generated vehicle trajectories are feasible, smooth and versatile. Our technique improves previous sinusoidal-based control works in terms of efficiency and flexibility. As further contributions, we present analytical expressions for the evolution of the robot's state, and propose a new state-feedback control law based on these expressions. All the information used in the control scheme is obtained from omnidirectional vision by means of the onedimensional trifocal tensor. Stability analysis of the proposed approach is presented, and its performance is illustrated through experiments.

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Visual control through the trifocal tensor for nonholonomic robots

Cited by 42 publications

References 31 publications

Adaptive dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot

Adaptive dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot

Exploiting the Trifocal Tensor in Dynamic Pose Estimation for Visual Control

Sinusoidal input-based visual control for nonholonomic vehicles

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