| 书目名称 | Collision Detection for Robot Manipulators: Methods and Algorithms |
| 编辑 | Kyu Min Park,Frank C. Park |
| 视频video | |
| 概述 | Provides a comprehensive survey on existing collision detection methods for robot manipulators.Includes both dynamics model-based and learning-based methods.Summarizes the fundamentals of collision de |
| 丛书名称 | Springer Tracts in Advanced Robotics |
| 图书封面 |  |
| 描述 | This book provides a concise survey and description of recent collision detection methods for robot manipulators. Beginning with a review of robot kinodynamic models and preliminaries on basic statistical learning methods, the book covers fundamental aspects of the collision detection problem, from collision types and collision detection performance criteria to model-free versus model-based methods, and the more recent data-driven learning-based approaches to collision detection. Special effort has been given to describing and evaluating existing methods with a unified set of notation, systematically categorizing these methods according to a basic set of criteria, and summarizing the advantages and disadvantages of each method. This book is the first to comprehensively organize the growing body of learning-based collision detection methods, ranging from basic supervised learning methods to more advanced approaches based on unsupervised learning and transfer learning techniques. Step-by-step implementation details and pseudocode descriptions are provided for key algorithms. Collision detection performance is measured with respect to both conventional criteria such as detection dela |
| 出版日期 | Book 2023 |
| 关键词 | Human-Robot Interaction; Robot Dynamics; Deep Learning; Mass Production; Artificial Intelligence; Collabo |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-30195-7 |
| isbn_softcover | 978-3-031-30197-1 |
| isbn_ebook | 978-3-031-30195-7Series ISSN 1610-7438 Series E-ISSN 1610-742X |
| issn_series | 1610-7438 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:06:35
