首页|Study Findings from Northeastern University Provide New Insightsinto Robotics (Sisg-net: Simultaneous Instance Segmentation and Grasp Detection for Robot Grasp In Clutter)
Study Findings from Northeastern University Provide New Insightsinto Robotics (Sisg-net: Simultaneous Instance Segmentation and Grasp Detection for Robot Grasp In Clutter)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Robotics. According to news reporting fromLiaoning, People’s Republic of China, by NewsRx journalists, research stated, “Robots have always foundit challenging to grasp in cluttered scenes because of the complex background in-formation and changingoperating environment. Therefore, in order to enable robots to perform multi-object grasping tasks ina wider range of application scenarios, such as object sorting on industrial production lines and objectmanipulation by home service robots, we innovatively integrated segmentation and grasp detection into the same framework, and designed a simultaneous instance segmentation and grasp detection network(SISG-Net).”
LiaoningPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsNortheastern University
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