首页|New Findings Reported from Leeds Beckett University Describe Advances in Robotics (Intelligent Robotics Harvesting System Process for Fruits Grasping Prediction)
New Findings Reported from Leeds Beckett University Describe Advances in Robotics (Intelligent Robotics Harvesting System Process for Fruits Grasping Prediction)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subject of a report. According to news originating from Leeds, United Kingdom, by NewsRx correspondents, research stated, “This paper proposes and executes an in-depth learning-based image processing approach for self-picking apples. The system includes a lightweight one-step detection network for fruit recognition.” Our news journalists obtained a quote from the research from Leeds Beckett University, “As well as computer vision to analyze the point class and anticipate a correct approach position for each fruit before grabbing. Using the raw inputs from a high-resolution camera, fruit recognition and instance segmentation are done on RGB photos. The computer vision classification and grasping systems are integrated and outcomes from tree-grown foods are provided as input information and output methodology poses for every apple and orange to robotic arm execution. Before RGB picture data is acquired from laboratory and plantation environments, the developed vision method will be evaluated. Robot harvest experiment is conducted in indoor as well as outdoor to evaluate the proposed harvesting system’s performance.” According to the news editors, the research concluded: “The research findings suggest that the pro- posed vision technique can control robotic harvesting effectively and precisely where the success rate of identification is increased above 95% in case of post prediction process with reattempts of less than 12%.”
LeedsUnited KingdomEuropeEmerging TechnologiesMa- chine LearningRoboticsRobotsLeeds Beckett University
NETL
NSTL
