A Real-time Range Finding System with Binocular Stereo Vision

To acquire range information for mobile robots, a TMS320DM642 DSP-based range finding system with binocular stereo vision is proposed. Firstly, paired images of the target are captured and a Gaussian filter, as well as improved Sobel kernels, are achieved. Secondly, a feature-based local stereo matching algorithm is performed so that the space location of the target can be determined. Finally, in order to improve the reliability and robustness of the stereo matching algorithm under complex conditions, the confidence filter and the left-right consistency filter are investigated to eliminate the mismatching points. In addition, the range finding algorithm is implemented in the DSP/BIOS operating system to gain real-time control. Experimental results show that the average accuracy of range finding is more than 99% for measuring single-point distances equal to 120cm in the simple scenario and the algorithm takes about 39ms for ranging a time in a complex scenario. The effectivity, as well as the feasibility, of the proposed range finding system are verified

Rapid tree model reconstruction for fruit harvesting robot system based on binocular stereo vision

In this paper, the method of spatial information extraction of tree branch was studied. The region matching method was used to get the disparity map of stereo image, extracted feature points combining with branch skeleton image by multi-segment approximation method, and calculated the spatial coordinates and the radius of branch feature points by using binocular stereo vision. Real-time model reconstruction for fruit tree has been researched on. Test proposed that each branch module was constructed by 12-prism in the coordinate origin, and then rotated twice and translated once to get correct posture, finally combined with other modules for the fruit tree model. Test has optimized extraction algorithm and matching algorithm of the branch region, improved matching rate, reduced matching errors, avoided matching confusion, accurately extracted branch spatial information and improved the success rate of robot path planning for obstacle avoidance

A berthing and fastening strategy for orbital replacement units

A summary of the GSFC applied research effort in robotic berthing is provided. The summary includes several demonstrations and experimental highlights illustrated on video. Two GSFC developments are central to the research, the 'Capaciflector' sensor and the 'Spline-Locking Screw fastener

Sensor Modeling Realization Based on Fruit Fly Optimization Algorithm

The structural parameter optimization model of binocular stereo vision sensor was first built using the optimum regression design to improve its measurement precision in this study. Then, the optimization model was solved by Fruit Fly Optimization Algorithm (FOA). The measurement precision of binocular stereo visual sensor has been greatly improved through FOA optimization. Thus, it can obtain better results than traditional methods

Surrounding moving obstacles detection using onboard binocular stereo vision

提出一种基于多视几何约束的车载双目立体视觉运动障碍检测算法。研究结果表明:多视极线约束有效地解决了当相机和障碍同方向运动时对极几何无法检测运动障碍的问题。在粒子滤波框架下,以多视极线约束为状态观测,可同时检测和跟踪多个运动障碍。不同场景实际数据集上的实验结果证明:该方法具有鲁棒性和有效性。A multiview epipolar constraint based algorithm was proposed for moving obstacles detection using onboard binocular stereo vision.The results show that a multiview epipolar constraint is derived from the relative camera positions in pairs of consecutive stereo views for independent motion detection.A dimensional variable particle filter for joint detection and tracking of multiple moving obstacles is presented.Experimental results on real-world driving sequences demonstrate that the method is effective and robust.教育部高等学校博士学科点专项科研基金资助项目(20124307120013