Robotics & Machine Learning Daily News2024,Issue(Jun.18) :5-6.

Reports Outline Robotics Findings from SRM Institute of Science and Technology ( Quicker Path Planning of a Collaborative Dualarm Robot Using Modified Bp-rrt* A lgorithm)

报告概述了SRM科学技术研究所的机器人研究结果(使用改进的BP-RT*A算法的协作双警报机器人的更快路径规划)

Robotics & Machine Learning Daily News2024,Issue(Jun.18) :5-6.

Reports Outline Robotics Findings from SRM Institute of Science and Technology ( Quicker Path Planning of a Collaborative Dualarm Robot Using Modified Bp-rrt* A lgorithm)

报告概述了SRM科学技术研究所的机器人研究结果(使用改进的BP-RT*A算法的协作双警报机器人的更快路径规划)

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摘要

由新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-关于机器人的详细数据已经呈现。Resea Rch根据NewsRx记者从印度钦奈发来的消息称:“工业机器人的路径规划是减少总体操作时间的重要任务。在工业任务中,路径规划是通过引导编程来执行的,在大多数情况下,机器人面对的是单一的对象配置。”我们的新闻记者从SRM科学技术研究所的研究中获得了一句话:“杂乱的环境需要路径规划算法,这是传感器驱动的,而不是预先编程的。路径规划算法,如RT,RRT*及其变种存在搜索持续时间长、生成多个节点样本等固有问题,导致路径长度变长.反向传播快速搜索随机树*(BP-RRT*)算法是一种在障碍物被球体包围时的飞跃.该方法利用三角形函数评价空间中路径与障碍物之间的联系,识别出空间中的非碰撞路径,预测出三维工作空间中最佳的非碰撞路径,目前的BP-RRT方法仅限于单臂机器人,协同双臂机器人比单臂机器人面临更多的路径规划问题。针对双臂协作机器人的网格预划分问题,提出了一种改进的BP-RT*算法,与传统的RT、RT*算法相比,该算法具有计算速度快、效率高、无碰撞等优点。改进后的RT*和BP-RT*算法在仿真和物理实现中得到了实现,与传统的RT方法相比,改进后的BP-RT*算法的典型路径长度分别减少了53.8%、6.95%、7.77%和6.83%。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on Robotics have been presented. Ac cording to news originating from Chennai, India, by NewsRx correspondents, resea rch stated, "Path-planning of an industrial robot is an important task to reduce the overall operation time. In industrial tasks, path planning is executed with lead-through programming, where in most cases the robot faces singulated object configurations." Our news journalists obtained a quote from the research from the SRM Institute o f Science and Technology, "Cluttered environments demand path-planning algorithm s, which are sensor driven, rather than pre-programmed. Path-planning algorithms , like RRT, and RRT* and their variants have inherent problems like the duration of a search and the creation of several node samples which may lead to longer p ath lengths. Back Propagation-Rapidly exploring Random Tree* (BP-RRT*) algorithm was a leap forward when an obstacle is enveloped with a sphere. Due to the sphe rical envelope of the obstacle, this method evaluates the connection between the path and obstacle in space with a spherical envelope using the triangular funct ion and identifies the non-collision path in 3D space. This predicts the best no n-collision path in the 3D workspace. The current state -of -the -art of BP-RRT* is limited to single -arm robots. A collaborative dual -arm robot faces more pr oblems in path planning than a single -arm robot like intercollision of manipul ator arms apart from avoiding obstacles. A Modified BP-RRT* algorithm is propose d for the dual -arm collaborative robot has a pre-stage partition of grids that makes the computation faster, efficient, and collision-free compared to the trad itional path planning algorithms namely RRT, RRT*, Improved RRT* and BP-RRT*. Th e algorithm is implemented in simulation as well as in physical implementation f or ABB YuMi dual -arm collaborative robot and the typical length of the path of the proposed modified BP-RRT* method has reduced by 53.8% from the traditional RRT method, 6.95% from the RRT* method, 7.77% from improved RRT* method and 6.83% from the BP-RRT* method."

Key words

Chennai/India/Asia/Algorithms/Emergi ng Technologies/Machine Learning/Robot/Robotics/SRM Institute of Science and Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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