基於多感測資訊於未知物體之智慧手抓取

Robot Intelligent Grasping for Unknown Objects based on Multi-Sensor Information

季善前(Shan-Qian Ji)

指導教授 ： 黃漢邦

國立臺灣大學/工學院/機械工程學研究所/碩士(2018年)

https://doi.org/10.6342/NTU201803004

摘要

通常機器人需要在人類環境中工作，並處理各種不同類型的物體，這會使機器人面臨兩個挑戰:人類環境通常是雜亂無章的，以及機器人需要在不知道物體重量，靜摩擦係數和剛性的情況下抓取和移動物體。因此，本文結合視覺和多指機械手動作，實現在雜亂的場景中對物體的抓取。並且根據包圍盒生成機械手無碰撞抓取姿態和路徑，並進一步檢查抓取姿態的抓取品質。最後，通過融合所有可用的感測器資料，實現智慧抓取系統，該系統能夠可靠處理各種未知重量，摩擦和剛性的物體。

關鍵字

機器手臂手掌系統 ； 抓取規劃 ； 感測器融合 ； 滑動檢測 ； 剛性測量

並列摘要

Robots usually need to work in human environments and handle many different types of objects. There are two problems that make this challenging for robots: Human environments are typically cluttered and the multi-finger robotic hand needs to grasp and lift objects without knowing their weight, coefficient of static friction, and stiffness. Thus, this thesis combines vision and robot hand action to achieve reliable and accurate object grasping in a cluttered scene. An efficient algorithm for collision-free grasping pose generation according to a bounding box is proposed and the grasp pose will be further checked for its grasp quality. Finally, by fusing all available sensor data appropriately, an intelligent grasp system is achieved that is reliable and enough to handle various objects with unknown weight, friction, and stiffness.

並列關鍵字

Robot Hand-Arm System ； Grasping Planning ； Sensor Fusion ； Slip Detection ； Stiffness Measurement

參考文獻

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