Month: May 2018

Distortion Invariant Joint-Feature for Visual Tracking in Catadioptric Omnidirectional Vision

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Abstract

Central catadioptric omnidirectional images exhibit serious nonlinear distortions due to quadratic mirrors involved. Conventional visual features developed based on the perspective model are hard to achieve a satisfactory performance when directly applied to the distorted omnidirectional image. This paper presents a parameterized neighborhood model to efficiently calculate the adaptive neighborhood of an object based on the measurable radial distance in image plane. On the basis of the parameterized neighborhood model, a distortion invariant joint-feature framework implemented with contour-color fragment mixture model of Gaussian is proposed for visual tracking in catadioptric omnidirectional camera system. Under the framework of Gaussian Mixture Model, the problem of feature matching is converted into feature clustering. A weight contribution mechanism is presented to flexibly weight the fragments based on their responses, which makes the system robustly guided by limited visible fragments even when serious partial occlusion happens. The experiments validate the performance of the proposed algorithm.

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Optimal teleoperation control of a constrained tendon-driven serpentine manipulator

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Abstract

In this paper, optimal remote control strategies to a novel master-slave flexible manipulator (FM) are presented. The system contains a constrained tendon-driven serpentine manipulator (CTSM), the base platform, a microcontroller, a PC and the Novint Falcon haptic input device. The bending of the CTSM backbone is controlled by the tendons and the length of the bending section is controlled by a constraint tube. Compared with other FMs, the CTSM has an improved workspace and dexterity. The CTSM is controlled using the Novint Falcon haptic input device, and two remote control modes are implemented, one is direct mapping and the other is incremental mode. Two optimal remote control strategies are proposed for the CTSM, i.e., highest stiffness and minimal movement. Experimental results show that the direct mapping is appropriated for fast movements and the incremental mode is adequate for accurate tasks. In combination with the optimal control strategies, a set of different applications for the CTSM are presented.

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Finding the Kinematic Base Frame of a Robot by Hand-Eye Calibration Using 3D Position Data

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Abstract
When a robot is required to perform specific tasks defined in the world frame, there is a need for finding the coordinate transformation between the kinematic base frame of the robot and the world frame. The kinematic base frame used by the robot controller to define and evaluate the kinematics may deviate from the mechanical base frame constructed based on structural features. Besides, by using kinematic modeling rules such as the product of exponentials (POE) formula, the base frame can be arbitrarily located, and does not have to be related to any feature of the mechanical structure. As a result, the kinematic base frame cannot be measured directly. This paper proposes to find the kinematic base frame by solving a hand-eye calibration problem using 3D position measurements only, which avoids the inconvenience and inaccuracy of measuring orientations and thus significantly facilitates practical operations. A closed-form solution and an iterative solution are explicitly formulated and proved effective by simulations. Comprehensive analyses of the impact of key parameters to the accuracy of the solution are also carried out, providing four guidelines to better conduct practical operations. Finally, experiments on a 7-DOF industrial robot are performed with an optical tracking system to demonstrate the superiority of the proposed method using position data only over the method using full pose data.
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A Novel Fiber Bragg Grating Displacement Sensor With a Sub-Micrometer Resolution

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Abstract

This paper has proposed a novel fiber Bragg grating (FBG) displacement sensor with a sub-micrometer resolution through the use of the transverse property of a suspended optical fiber with a pre-tension force. A wedge-shaped sliding block and a T-shaped cantilever beam formed a conversion mechanism to transfer the horizontal measured-displacement into the transverse movement of the optical fiber midpoint. Compared with existing FBG displacement sensors, this design does not only avoid the FBG-pasting process and its associated issues such as, the chirping failure and low repeatability, but also achieves a high resolution. The sensing principle has been presented, and the corresponding theoretical model has been derived and validated. Experiments show that this design has an excellent sensitivity of 2086.27 pm/mm and a high resolution of 0.48 μm within a range of 1.0~2.0 mm. The displacement results from the proposed sensor closely agree with the values detected from the commercial laser displacement sensor, validating its effectiveness. Therefore, the proposed sensor can be directly utilized to measure the sub-micrometer displacement, and also support multi-point distributed detection.

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