首页|Research from Indian Council of Agricultural Research (ICAR) Indian Agricultural Statistics Research Institute in the Area of Robotics Published (Pony: Leveragi ng m-Graphs and Pruned-BFS Algorithm to Elevate AI-Powered Low-Cost Self-Driving ...)
Research from Indian Council of Agricultural Research (ICAR) Indian Agricultural Statistics Research Institute in the Area of Robotics Published (Pony: Leveragi ng m-Graphs and Pruned-BFS Algorithm to Elevate AI-Powered Low-Cost Self-Driving ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in robotics. A ccording to news reporting out of New Delhi, India, by NewsRx editors, research stated, “In industrial environments, efficient indoor transportation is a corner stone of streamlined operations. However, the availability of high-end robotic t ransportation systems often poses a challenge for small-scale manufacturers due to their prohibitive costs.” The news correspondents obtained a quote from the research from Indian Council o f Agricultural Research (ICAR) Indian Agricultural Statistics Research Institute : “Addressing this disparity, this research introduces ‘Pony’, an innovative and cost-effective semi-autonomous self-driven robotic system tailored for indoor t ransportation purposes. Built upon a microcontroller-based platform, Pony harnes ses low-cost technology to create and store m-graphs effectively, facilitating s eamless navigation within indoor facilities. Moreover, the study presents a nove l Pruned-BFS (P-BFS) algorithm designed to efficiently traverse mgraphs, outper forming conventional graph-traversal approaches. Furthermore, the experimental v alidation in the study encompasses a comprehensive evaluation of Pony’s performa nce across a range of scenarios. Randomly generated graphs, varying in complexit y from 26 to 200 nodes, serve as the testing ground. Notably, four distinct algo rithms-Breadth First Seach (BFS), Depth First Search (DFS), Iterative DFS (ID), and P-BFS are put through their paces during numerous random walks on each graph .”
Indian Council of Agricultural Research (ICAR) Indian Agricultural Statistics Research InstituteNew DelhiIndiaAsiaAlgorithmsEmerging TechnologiesMachine LearningRoboticsRobots
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