局部可视环境中基于视觉和触觉感知的灵巧手精细操作的方法研究

项目名称： 局部可视环境中基于视觉和触觉感知的灵巧手精细操作的方法研究

项目编号： No.61503095

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化学科

项目作者： 张元飞

作者单位： 哈尔滨工业大学

项目金额： 21万元

中文摘要： 以模拟人类在局部可视环境中对目标物体进行识别和操作为背景，解决与知识库构建、混合智能模型构建和灵巧手自主操作策略相关的关键科学问题。首先，基于物体局部区域为弹性和阻尼模型假设，提出面向灵巧手操作的物体局部接触特征选定和提取方法，利用聚类算法构建接触特征知识库，实现了接触特征知识库中的数据在识别和操作两阶段复用目标；然后，构建基于D-S证据理论和模糊神经网络混合智能模型，融合视觉和触觉信息，实现期望目标物体识别、相对位姿估计和灵巧手精细操作性能评价。为解决局部可视环境中疑似目标轮廓特征提取的有效性和快速性兼顾问题，基于视觉引导主动触觉感知的可变步长搜索策略，提出了基于视觉和触觉信息融合的物体局部轮廓信息重构及特征提取算法；最后，为了实现物体操作性能的在线提升，基于拟人操作知识库规划灵巧手手指运动，提出了基于操作性能评价指标反馈的接触力自适应阻抗控制策略。

中文关键词： 多传感器信息融合；触觉感知；目标识别；自适应控制；多指操作

英文摘要： In order to simulate the human behavior of a target object recognition and manipulation in the local visual environment, some key scientific questions related to knowledge base construction，hybrid intelligent model construction and autonomous operation strategy of dexterous hand are proposed and solved in this project. First, to achieve the goal that the data coming from a knowledge base of the contact characteristic can be used in both stages, identification stage and operation stage, some methods of selecting and extracting contact features are proposed based on the hypothesis that the contact model of object local area is a elasticity and damping model. And the knowledge base of the contact features is constructed by using clustering algorithm; Then, a DS evidence theory and fuzzy neural network based hybrid intelligent model is constructed based on visual and tactile information fusion, to achieve target recognition of a desired object, relative pose estimation between the dexterous hand and the target object and performance evaluation of the dexterous hand operating the target object. In order to meet the validity and rapidity of contour feature extraction of a suspected target in complex environment, an algorithm of local contour reconstruction and feature extraction is proposed based on the fusion of visual and tactile information. During reconstruction, a variable step size search strategy based on active tactile perception under vision guided is adopted. At last, to improve the online manipulation performance of the object, the finger movement is planned based on a knowledge base of anthropomorphic operation, and an adaptive impedance control strategy of the contact force based on the feedback of operation performance evaluation index is proposed.

英文关键词： multi-sensor information fusion;tactile perception;target recognition;adaptive control;multifinger manipulation