¡¡¡¡ÖÐÐÂÍø¸£½¨ÐÂÎÅ4ÔÂ9ÈÕµç(ÔøÃîÁä ÖÙѵê½)ÏÃÃÅÀí¹¤Ñ§ÔºµçÆø¹¤³ÌÓë×Ô¶¯»¯Ñ§ÔºÖÙѵ꽸±½ÌÊÚÍŶӾ۽¹¡°»úÆ÷ÈËÈÎÎñÀí½âÓëÈÎÎñ²Ù×÷¡±Ñо¿Ç°ÑØ£¬½üÈÕÔÚ¹ú¼Ê¶¥¼¶ÆÚ¿¯IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING(¡¶IEEE×Ô¶¯»¯¿ÆÑ§Ó빤³Ì»ã¿¯¡·£¬Ó°ÏìÒò×Ó5.9)ÓëIEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT(¡¶IEEEÒÇÆ÷ÒDZíÓë²âÁ¿»ã¿¯¡·£¬Ó°ÏìÒò×Ó5.6)·¢±íÁ½Æª¸ßˮƽÂÛÎÄ¡£
¡¡¡¡ÕâÊǸÃÍŶÓÔÚ»úÆ÷ÈËÖÇÄܼ¼ÊõÁìÓòµÄÓÖÒ»±êÖ¾ÐԳɹû¡£
¡¡¡¡ÏÃÃÅÀí¹¤Ñ§Ôº9ÈÕ½éÉÜ£¬ÖÙѵê½ÍŶÓÓë¹úÄÚÍâÖªÃûѧ¸®ºÏ×÷£¬ÉîÈëÑо¿»úÆ÷ÈË»ù´¡ÀíÂÛÓëÓ¦Óá£ÂÛÎÄRIGNet: Robot Intention Grasp for Dense Stacked Targets With Multi-Task Siamese Schema Through RoIs Learning(¡¶RIGNet£º»ùÓÚ¶àÈÎÎñÂÏÉú¿ò¼ÜÓë¸ÐÐËÈ¤ÇøÓòѧϰµÄ»úÆ÷ÈËÃܼ¯¶ÑµþÄ¿±êÒâͼץȡÑо¿¡·)ºÍSS-ARGNet: A Novel Cascaded Schema for Robots¡¯7-DoF Grasping in Adjacent and Stacked Object Scenarios(¡¶SS-ARGNet£ºÒ»ÖÖÓÃÓÚÏàÁÚ¼°¶ÑµþÎïÌ峡¾°µÄ»úÆ÷ÈËÆß×ÔÓɶÈץȡÐÂÐͼ¶Áª¼Ü¹¹¡·)·Ö±ð̽ÌÖÁ˶àÈÎÎñÂÏÉúÉî¶ÈÍøÂç¼°»úÆ÷ÈËÒâͼ²Ù×÷£¬ÒÔ¼°ÃæÏò¸´ÔÓ¹¤¼þµÄ»úÆ÷ÈËBIN-PICKINGͨÓÃAI¼¼Êõ£¬¾ù»ñµÃ¹ú¼Êר¼Ò¸ß¶ÈÆÀ¼Û£¬²¢ÓÐÆóÒµ¼¼ÊõתÈÃÒâÏò¡£
¡¡¡¡´Ëǰ£¬¸ÃÍŶӽ«¿ÆÑгɹûÓ¦ÓÃÓÚ¡°ÏÖ´úÎÞÈ˼ÝÊ»²æ³µÏµÍ³¡±£¬¹¥¿Ë¹Ø¼ü¼¼ÊõÄÑÌâ£¬ÍÆ¶¯ÆóÒµ²úÆ·µü´úÉý¼¶£¬»ñ2024Äê¶ÈÏÃÃÅÊпÆÑ§¼¼Êõ½ø²½½±¶þµÈ½±¡£
¡¡¡¡¾Ý½éÉÜ£¬ÍŶÓ×¢ÖØ¿ÆÑ§Ñо¿Óëѧ¿Æ½¨ÉèÏà½áºÏµÄÈ˲ÅÅàÑøÄ£Ê½£¬½üÄêÀ´ÂÅ»ñ¹úÄÚÍâ½±ÏѧÉú²ÎÓë¿ÎÌâÑо¿£¬·¢±í¶àƪÂÛÎÄ£¬È¡µÃÊÚȨ·¢Ã÷רÀû£¬±ÏÒµÉúרҵ¶Ô¿Ú¾ÍÒµÂʸߴï95%¡£(Íê)