Vision-based path following using the 1D trifocal tensor

Sabatta, Deon; Siegwart, Roland

doi:10.1109/icra.2013.6631007

Cited by 9 publications

(12 citation statements)

References 17 publications

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“…The concatenation of the three 3⇥3 matrices i.e., T 1 , T 2 , and T 3 defines the trifocal tensor T 3⇥3⇥3 . One can remark that the formula (8) is generally inappropriate for the design of control laws because it involves several complex matrix (respectively, tensors) manipulations, numerical approximations and matrices and tensors inversions [22]. As a result, we have revisited the trifocal constraint by making an analogy between a three-camera system and a two-camera + laser scanner system [19].…”

Section: Revisited Three-view Geometrymentioning

confidence: 99%

Laser Beam Steering Along Three-Dimensional Paths

Tamadazte

Renevier

Seon

et al. 2018

IEEE/ASME Trans. Mechatron.

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This paper deals with the development of a visionbased control scheme for 3D laser steering. It proposes to incorporate a simplified trifocal constraint inside a path following scheme in order to ensure intuitively a 3D control of laser spot displacements in unknown environment (target). The described controller is obtained without complex mathematical formulation nor matrix inversion as it requires only weak camera and hand-eye calibration. The developed control law was validated in both simulation and experimental conditions using various scenarios (e.g., static and deformable 3D scenes, different control gains, initial velocities, etc.). The obtained results exhibit good accuracy and robustness with respect to the calibration and measurement errors and scene variations. In addition, with this kind of laser beam steering controller, it becomes possible to perfectly decouple the laser spot velocity from both the path shape and time. These features can fit several industrial applications (welding, micromachining, etc.) as well as surgical purposes (e.g., laser surgery) requirements. • a geometric task, which consists of approaching the robot to the desired curve, • a dynamic assignment task, which assigns a velocity profile (instead of time) to the desired curve.

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Section: Revisited Three-view Geometrymentioning

confidence: 99%

Laser Beam Steering Along Three-Dimensional Paths

Tamadazte

Renevier

Seon

et al. 2018

IEEE/ASME Trans. Mechatron.

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“…After taking the time derivative of (23) and exploiting (16), (17), and Property 1, it can be concluded thaṫ…”

Section: Stability Analysismentioning

confidence: 99%

“…Due to this fact, the trifocal tensor has great potential in addressing visual servoing [13]. Most of the existing trifocal tensor based methods focus on controlling a nonholonomic mobile robot to achieve different tasks, mainly including regulation [12], [14], [15], path following [16], and trajectory tracking [17]. In [12], by considering the planar motion constraint, a subset of the trifocal tensor is utilized to regulate a mobile robot toward a desired pose.…”

Section: Introductionmentioning

confidence: 99%

Visual Servoing with Trifocal Tensor

Zhang

Chen

Chaumette

2018

2018 IEEE Conference on Decision and Control (CDC)

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In this paper, a trifocal tensor-based approach is developed for 6 degrees-of-freedom visual servoing. The trifocal tensor model among the current, desired, and initial views is introduced to describe the geometric relationship. Then, the tensor elements are refined to construct the visual feedback without resorting to explicit estimation of the camera pose. Based on the extracted tensor features, an adaptive controller is designed to drive the camera to a desired pose and compensate for the unknown distance scale factor. Moreover, Lyapunovbased techniques are exploited to analyze the system stability and convergence domain. Simulation results are provided to demonstrate the effectiveness of the developed approach.

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“…Due to this fact, the trifocal tensor has great potential in addressing visual servoing (Andreff and Tamadazte, 2016;Chen et al, 2018). The trifocal tensor based visual servoing can be divided into 1-D methods (Becerra and Sagüés, 2013;Sabatta and Siegwart, 2013) and 2-D ones (López-Nicolás et al, 2010;Chen et al, 2017). Most of these methods focus on controlling a nonholonomic wheeled mobile robot to achieve different tasks, mainly including regulation (Becerra and Sagüés, 2013;López-Nicolás et al, 2010), path following (Sabatta and Siegwart, 2013), and trajectory tracking (Chen et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…There are distinct differences between this paper and the existing trifocal tensor based works (Becerra and Sagüés, 2013;Sabatta and Siegwart, 2013;López-Nicolás et al, 2010;Chen et al, 2017;Shademan and Jägersand, 2010). First, this paper considers the 6 DOF eye-in-hand visual regulation, while Becerra and Sagüés (2013); Sabatta and Siegwart (2013);López-Nicolás et al (2010); Chen et al (2017) focus on the 3 DOF vision-based control of ground mobile robots. Second, instead of constructing the visual system with simplified 1-D trifocal tensor as Becerra and Sagüés (2013); Sabatta and Siegwart (2013), the 2-D trifocal tensor is utilized in this paper to describe the visual model, which is more suitable for the 6 DOF visual servoing.…”

Section: Introductionmentioning

confidence: 99%

Trifocal tensor-based 6-DOF visual servoing

Zhang

Chaumette

Chen

2019

The International Journal of Robotics Research

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This paper proposes a trifocal tensor-based approach for six-degree-of-freedom visual servoing. The trifocal tensor model among the current, desired, and reference views is constructed to describe the geometric relationship of the system. More precisely, to ensure the computation consistency of trifocal tensor, a virtual reference view is introduced by exploiting the transfer relationships between the initial and desired images. Instead of resorting to explicit estimation of the camera pose, a set of visual features with satisfactory decoupling properties are constructed from the tensor elements. Based on the selected features, a visual controller is developed to regulate the camera to a desired pose, and an adaptive update law is used to compensate for the unknown distance scale factor. Furthermore, the system stability is analyzed via Lyapunov-based techniques, showing that the proposed controller can achieve almost global asymptotic stability. Both simulation and experimental results are provided to demonstrate the effectiveness and robustness of our approach under different conditions and case studies.

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Vision-based path following using the 1D trifocal tensor

Cited by 9 publications

References 17 publications

Laser Beam Steering Along Three-Dimensional Paths

Laser Beam Steering Along Three-Dimensional Paths

Visual Servoing with Trifocal Tensor

Trifocal tensor-based 6-DOF visual servoing

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