基于表面凹凸度的未知物体分割识别方法

为了使机器人在人们的生活中更加普及和大众化,并从一定程度上优化机器人对周围环境的认知功能,设计了一种利用目标物体表面凹凸度对该物体进行分割识别的方法.该方法对目标物体局部表面凹凸性的两类判定方法展开了系统性的探讨和分析,将连续局部表面凹凸度对布尔型判定进行替换,利用表面凹凸度和法方向信息这两个要素设计了一类全新的分割权重运算方法,进而为输入场景构造相应的无向带权图,在这之后结合快速图分割算法获得相应的目标物体.实验结果表明,本文方法与基于凹凸性的判定方式相比,基于凹凸度的量化衡量在针对测量噪声和计算误差中具有的鲁棒性更好,实际分割结果比单一结合了法方向的实验结果好,更符合实践需求.

Segmentation and Recognition Method of Unknown Object Based on Surface Roughness

In order to improve the speed of the robot in the daily life and improve the robot''s cognitive environment, a scheme is proposed to detect unknown objects by means of the object surface roughness. This method launches a systematic method for determining discussion and analysis for local surface irregularities of the two type determining method for target objects, replaces the determination of Boolean to the continuous local surface irregularities, uses the two elements of that surface irregularities and law degree direction information to design a new class of segmentation weight calculation method, and then enter the scene to construct corresponding undirected weighted graph, after this, combines fast graph partitioning algorithm to obtain the corresponding target object. The experimental results show that: compared to the judgment method based on the irregularities convexity, the robustness of the method is better than that of the observation noise and the estimation error, the performance of the proposed method is sufficient to meet the needs of the practice based on the complexity of learning and reasoning methods, it is more in line with the needs of practice.