期刊
ROBOTICS AND AUTONOMOUS SYSTEMS
卷 167, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.robot.2023.104484
关键词
Collision detection; Rapidly-exploring random tree; Motion planning; Manipulator; Machine learning
The application of artificial intelligence tools has led to the development of collision detectors with better computational efficiency than kinematics-and-geometry based collision detectors (KCD) for improving robot motion planning strategies. However, the new detectors lack accuracy in certain cases. To enhance accuracy, a trade-off between efficiency and accuracy is needed. We propose a novel compound collision detector (CCD) that modifies the planners of rapidly-exploring random tree (RRT) to improve the classical probabilistic collision detector (PCD). This CCD consists of an exact collision detector (ECD), an inference collision detector (ICD), and a strategy to determine the use of ECD or ICD based on certain conditions. Experimental evaluation on a Kinova Jaco assistive robotic arm demonstrates improved accuracy with a slight reduction in speed compared to PCD, making the CCD a promising tool in robot motion planning.
The application of artificial intelligence tools has led to newly developed collision detectors which have better computational efficiency than the kinematics-and-geometry based collision detectors (KCD) to improve robot motion planning strategies. However, new detectors are not very accurate in some cases. To improve the accuracy, a trade-off between efficiency and accuracy is required. We propose a novel compound collision detector (CCD) for collision queries that modifies the planners of rapidly-exploring random tree (RRT) to improve the classical probabilistic collision detector (PCD). It is composed of an exact collision detector (ECD), an inference collision detector (ICD) and a strategy to determine ECD or ICD based on some conditions. In our CCD, we use a sphere-ellipsoidal pseudo distance (SEPD) in the determination strategy to alleviate the problem of highly-frequent outputs of false-positive in narrow passages of PCD, and a node based bounding method (NBB) to increase the speed of data storage and loading for the sub-algorithm ICD. Experiments on a Kinova Jaco assistive robotic arm are taken to evaluate the performance of our CCD, which show an improved accuracy with a small reduction of speed in comparison with PCD. So, it is a promising tool in robot motion planning.& COPY; 2023 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据