BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Australia/Brisbane BEGIN:STANDARD DTSTART:19920301T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 TZNAME:AEST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20221103T130256Z UID:64F96013-A319-48A6-8A65-14A4E9846825 DTSTART;TZID=Australia/Brisbane:20220701T110000 DTEND;TZID=Australia/Brisbane:20220701T120000 DESCRIPTION:CSIRO's Robotics and Autonomous Systems Group is hosting Prof. Michael Wang and Dr. Chao Chen from Monash University for a combined semin ar on agriculture robotics and adaptive grasping.\n\n[Michael Yu Wang] Ada ptive Grasping with Touch Sensing and Dry-Adhesive Contact\n\nAbstract: In the field of robotic manipulation\, touch sensing and contact adhesion ha ve been considered as essential techniques for versatile capabilities of a daptive grasping and manipulation. Thanks to respective advances in optica l tactile sensors and in scalable fabrication of gecko-inspired dry adhesi ve skins\, these distinctive techniques continue to be developed. Moreover \, complementary sense of touch and adaptive contact can be integrated int o a robotic gripper. As such\, touch sensing is endowed into a gecko-gripp er for the promise of adaptive grasping.\n\nIn this presentation\, I will review our work on optical touch sensing and adhesive contact skins. Our d eformable sensor provides high-resolution real-time measurements of contac t area and contact shear force. Gecko-inspired dry-adhesive skins are read ily integrated on the sensor surface\, providing variable adhesion and fri ction. I will showcase the gripper’s ability to adjust fingertip pose fo r better contact using sensor feedback\, especially for top-side gripping onto a nearly flat surface (smooth or rough) of an object with firm attach ment. I will show practical applications in industrial automation and disc uss the recent developments throughout the robotics community advancing in this promising direction.\n\nBio: Michael Yu Wang is a Professor and the Head of Department of Mechanical and Aerospace Engineering of Monash Unive rsity. Before joining Monash University in 2022\, he was the Founding Dire ctor of HKUST’s Cheng Kar-Chun Robotics Institute. He also served on the engineering faculty at University of Maryland\, Chinese University of Hon g Kong\, and National University of Singapore. He has numerous professiona l honors–Kayamori Best Paper Award of 2001 IEEE International Conference on Robotics and Automation\, the Compliant Mechanisms Award-Theory of ASM E 31st Mechanisms and Robotics Conference in 2007\, Research Excellence Aw ard (2008) of CUHK\, and ASME Design Automation Award (2013). He is the cu rrent Editor-in-Chief of IEEE Trans. on Automation Science and Engineering \, and served as an Associate Editor of IEEE Trans. on Robotics and Automa tion and ASME Journal of Manufacturing Science and Engineering. He is a Fe llow of ASME\, HKIE and IEEE. He received his Ph.D. degree from Carnegie M ellon University.\n\n[Chao Chen] The Monash Apple Retrieving System (MARS) \n\nAbstract: Farmers and fruit growers have acknowledged the need to adop t smart technologies and automation on their farms to combat the growing c oncern of manual labour shortages\, with estimated losses of over $38 mill ion per year attributed to unharvested crops in Australia. Selective harve sting of high value crops such as fruits and vegetables is a very labour-i ntensive and expensive task\, which makes it a good candidate for robotic automation. This need has driven significant research and investments in a utomated harvesting robots recently\, leading to advancements in vision an d fruit detection algorithms\, innovative robot designs\, and fruit extrac tion mechanisms. However\, adoption of these robots among farmers remains low\, due to significant technical challenges in handling complex canopy e nvironments.\n\nIn this presentation\, I will introduce our apple harvesti ng robot developed in my laboratory LMGA\, called the Monash Apple Retriev ing System (MARS) which can harvest up to 8 apples per minute in complex y et typical canopy environments. The robot features a six degree of freedom robotic arm for dexterous harvesting\, a vision system capable of real ti me detection of apples in an occluded environment\, and soft gripper to ex tract difficult-to-reach fruit from within the canopy without damage. The system is integrated with fruit pose estimation and intelligent planning a lgorithms to optimise harvesting performance. Our technologies and algorit hms allow MARS to harvest non-destructively with high precision\, which wi ll appeal to many local farmers who are concerned about significant canopy damage that can be caused by robotic harvesters.\n\nBio: Chao Chen is a S enior Lecturer in the Department of Mechanical and Aerospace Engineering o f Monash University. He is also an Adjunct Associate Professor at the Chin ese University of Hong Kong. He established the Laboratory of Motion Gener ation and Analysis and is the founding academic and supervisor of Monash N ova Rover Team. He received the 2022 Award of Editor’s Choice Article by Sensors\, the 2020 Superior Paper Award by Computers and Electronics in A griculture\, and the 2017 Innovation Award by Australian Hand Therapy Asso ciation. His Nova Rover Team achieved the 2nd Place in University Rover Ch allenge at Mars Desert Research Station in Utah in 2022. He is currently t he Editor of Agronomy: Precision and Digital Agriculture. He received his Ph.D. degree from McGill University.\n\nCo-sponsored by: CSIRO's Robotics and Autonomous Systems Group\n\nSpeaker(s): Michael Wang\, \n\nVirtual: ht tps://events.vtools.ieee.org/m/317540 LOCATION:Virtual: https://events.vtools.ieee.org/m/317540 ORGANIZER:navinda.kottege@csiro.au SEQUENCE:2 SUMMARY:[CSIRO RAS Seminar] Agriculture Robotics and Adaptive Grasping URL;VALUE=URI:https://events.vtools.ieee.org/m/317540 X-ALT-DESC:Description: <br /><p>CSIRO's Robotics and Autonomous Systems Gr oup is hosting Prof. Michael Wang and Dr. Chao Chen from Monash University for a combined seminar on agriculture robotics and adaptive grasping.</p> \n<p>[<strong>Michael Yu Wang</strong>] Adaptive Grasping with Touch Sensi ng and Dry-Adhesive Contact</p>\n<p><strong>Abstract:</strong> In the fiel d of robotic manipulation\, touch sensing and contact adhesion have been c onsidered as essential techniques for versatile capabilities of adaptive g rasping and manipulation. Thanks to respective advances in optical tactile sensors and in scalable fabrication of gecko-inspired dry adhesive skins\ , these distinctive techniques continue to be developed. Moreover\, comple mentary sense of touch and adaptive contact can be integrated into a robot ic gripper. As such\, touch sensing is endowed into a gecko-gripper for th e promise of adaptive grasping.</p>\n<p>In this presentation\, I will revi ew our work on optical touch sensing and adhesive contact skins. Our defor mable sensor provides high-resolution real-time measurements of contact ar ea and contact shear force. Gecko-inspired dry-adhesive skins are readily integrated on the sensor surface\, providing variable adhesion and frictio n. I will showcase the gripper&rsquo\;s ability to adjust fingertip pose f or better contact using sensor feedback\, especially for top-side gripping onto a nearly flat surface (smooth or rough) of an object with firm attac hment. I will show practical applications in industrial automation and dis cuss the recent developments throughout the robotics community advancing i n this promising direction.</p>\n<p><strong>Bio:</strong> Michael Yu Wang is a Professor and the Head of Department of Mechanical and Aerospace Engi neering of Monash University. Before joining Monash University in 2022\, h e was the Founding Director of HKUST&rsquo\;s Cheng Kar-Chun Robotics Inst itute. He also served on the engineering faculty at University of Maryland \, Chinese University of Hong Kong\, and National University of Singapore. He has numerous professional honors&ndash\;Kayamori Best Paper Award of 2 001 IEEE International Conference on Robotics and Automation<em>\, </em>th e Compliant Mechanisms Award-Theory of ASME 31<sup>st</sup> Mechanisms and Robotics Conference in 2007\, Research Excellence Award (2008) of CUHK\, and ASME Design Automation Award (2013). He is the current Editor-in-Chief of IEEE Trans. on Automation Science and Engineering\, and served as an A ssociate Editor of IEEE Trans. on Robotics and Automation and ASME Journal of Manufacturing Science and Engineering. He is a Fellow of ASME\, HKIE a nd IEEE. He received his Ph.D. degree from Carnegie Mellon University. &nb sp\;</p>\n<p>&nbsp\;</p>\n<p>[<strong>Chao Chen</strong>] The Monash Apple Retrieving System (MARS)</p>\n<p><strong>&nbsp\;Abstract:</strong> Farmer s and fruit growers have acknowledged the need to adopt smart technologies and automation on their farms to combat the growing concern of manual lab our shortages\, with estimated losses of over $38 million per year attribu ted to unharvested crops in Australia. Selective harvesting of high value crops such as fruits and vegetables is a very labour-intensive and expensi ve task\, which makes it a good candidate for robotic automation. This nee d has driven significant research and investments in automated harvesting robots recently\, leading to advancements in vision and fruit detection al gorithms\, innovative robot designs\, and fruit extraction mechanisms. How ever\, adoption of these robots among farmers remains low\, due to signifi cant technical challenges in handling complex canopy environments.</p>\n<p >In this presentation\, I will introduce our apple harvesting robot develo ped in my laboratory LMGA\, called the Monash Apple Retrieving System (MAR S) which can harvest up to 8 apples per minute in complex yet typical cano py environments. The robot features a six degree of freedom robotic arm fo r dexterous harvesting\, a vision system capable of real time detection of apples in an occluded environment\, and soft gripper to extract difficult -to-reach fruit from within the canopy without damage. The system is integ rated with fruit pose estimation and intelligent planning algorithms to op timise harvesting performance. Our technologies and algorithms allow MARS to harvest non-destructively with high precision\, which will appeal to ma ny local farmers who are concerned about significant canopy damage that ca n be caused by robotic harvesters.</p>\n<p><strong>Bio:</strong> Chao Chen is a Senior Lecturer in the Department of Mechanical and Aerospace Engine ering of Monash University. He is also an Adjunct Associate Professor at t he Chinese University of Hong Kong. He established the Laboratory of Motio n Generation and Analysis and is the founding academic and supervisor of M onash Nova Rover Team. He received the 2022 Award of Editor&rsquo\;s Choic e Article by Sensors\, the 2020 Superior Paper Award by Computers and Elec tronics in Agriculture\, and the 2017 Innovation Award by Australian Hand Therapy Association. His Nova Rover Team achieved the 2<sup>nd</sup> Place in University Rover Challenge at Mars Desert Research Station in Utah in 2022. He is currently the Editor of Agronomy: Precision and Digital Agricu lture. He received his Ph.D. degree from McGill University.</p> END:VEVENT END:VCALENDAR