Accurate 3D Reconstruction of Dynamic Objects by Spatial-Temporal Multiplexing and Motion-Induced Error Elimination.

Three-dimensional (3D) reconstruction of dynamic objects has broad applications, including object recognition and robotic manipulation. However, achieving high-accuracy reconstruction and robustness to motion simultaneously is a challenging task. In this paper, we present a novel method for 3D reconstruction of dynamic objectS, whose main features are as follows. Firstly, a structured-light multiplexing method is developed that only requires 3 patterns to achieve high-accuracy encoding. Fewer projected patterns require shorter image acquisition time, thus, the object motion is reduced in each reconstruction cycle. The three patterns, i.e. spatial-temporally encoded patterns, are generated by embedding a specifically designed spatial-coded texture map into the temporal-encoded three-step phase-shifting fringes. A temporal codeword and three spatial codewords are extracted from the composite patterns using a proposed extraction algorithm. The two types of codewords are utilized separately in stereo matching: the temporal codeword ensures the high accuracy, while the spatial codewords are responsible for removing phase ambiguity. Secondly, we aim to eliminate the reconstruction error induced by motion between frames abbreviated as motion induced error (MiE). Instead of assuming the object to be static when acquiring the 3 images, we derive the motion of projection pixels among frames. Using the extracted spatial codewords, correspondences between different frames are found, i.e. pixels with the same codewords are traceable in the image sequences. Therefore, we can obtain the phase map at each image-acquisition moment without being affected by the object motion. Then the object surfaces corresponding to all the images can be recovered. Experimental results validate the high reconstruction accuracy and precision of the proposed method for dynamic objects with different motion speeds. Comparative experiments show that the presented method demonstrates superior performance with various types of motion, including translation in different directions and deformation.

3D reconstruction of objects with occlusion and surface reflection using a dual monocular structured light system.

Three-dimensional (3D) vision plays an important role in industrial vision, where occlusion and reflection have made it challenging to reconstruct the entire application scene. In this paper, we present a novel 3D reconstruction framework to solve the occlusion and reflection reconstruction issues in complex scenes. A dual monocular structured light system is adopted to obtain the point cloud from different viewing angles to fill the missing points in the complex scenes. To enhance the efficiency of point cloud fusion, we create a decision map that is able to avoid the reconstruction of repeating regions of the left and right system. Additionally, a compensation method based on the decision map is proposed for reducing the reconstruction error of the dual monocular system in the fusion area. Gray-code and phase-shifting patterns are utilized to encode the complex scenes, while the phase-jumping problem at the phase boundary is avoided by designing a unique compensation function. Various experiments including accuracy evaluation, comparison with the traditional fusion algorithm, and the reconstruction of real complex scenes are conducted to validate the method's accuracy and the robustness to the shiny surface and occlusion reconstruction problem.

Energy-efficient control of a screw-drive pipe robot with consideration of actuator's characteristics.

Pipe robots can perform inspection tasks to alleviate the damage caused by the pipe problems. Usually, the pipe robots carry batteries or use a power cable draining power from a vehicle that has many equipments for exploration. Nevertheless, the energy is limited for the whole inspection task and cannot keep the inspection time too long. In this paper, we use the total input energy as the cost function and a more accurate DC motor model to generate an optimal energy-efficient velocity control for a screw-drive pipe robot to make use of the limited energy in field environment. We also propose a velocity selection strategy that includes the actual velocity capacity of the motor, according to the velocity ratio [Formula: see text], to keep the robot working in safe region and decrease the energy dissipation. This selection strategy considers three situations of the velocity ratio [Formula: see text] and has a wide range of application. Simulations are conducted to compare the proposed method with the sinusoidal control and loss minimization control (minimization of copper losses of the motor), and results are discussed in this paper.