INSIGHTS
NEWS
Machine learning, machine vision: Robot helps stop COVID-19 spread For robots on wheels, narrower, shal- to perform this task,” Nguyen said. lower spaces, like between desks in a LASER-D has been tested around camclassroom or on stairwells, wheels can be pus. While LASER-D is not yet autonolimiting. LASER-D (Legged Agile Smart mous, increased autonomy and increased Efficient Robot for Disinfection) is a four- distance between the human operator and legged robot created by a team of USC the robot are long-term development goals. researchers at the USC Viterbi School of Said master’s student Abhinav PanEngineering. LASERdey, “Like a human, SEE VIDEO ONLINE D (Legged Agile the system should be Smart Efficient Robot able to identify what Just two images were for Disinfection ) a has to be disinfectused for training, instead of four-legged robot ed, whether or not created by a team of the disinfection took using 50,000 images. USC researchers at place properly durthe USC Viterbi School of Engineering. ing the first round, and whether or not the The robot combines locomotive agility and robot should move on or perform a second chemical disinfection to fight COVID-19, round of disinfection.” These are targets of among other applications. a future version. “This is the first time we’ve combined With LASER-D’s ability to move while a legged robot with the disinfection task,” spraying, the team believes it could be usesaid Quan Nguyen, an assistant professor ful in different areas, including agriculture. of aerospace and mechanical engineering. “A robot like LASER-D could perform This can be challenging, because we need very localized agricultural tasks like preto maintain mobility while positioning for cision pesticide dispensing or precision disinfection. LASER-D conserves energy irrigation,” said SK Gupta, Smith Internaby walking and positioning its body simul- tional Professor of Mechanical Engineertaneously. Thus, we can just use the robot ing and Computer Science. orientation to control the spraying of disCleaning applications that focus less infectant, instead of attaching an extra arm on disinfection and more on aesthetics
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Collaborative robot market surge
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nteract Analysis’ report on the collaborative robot market indicates there is optimism with significant growth predicted over the next decade after a rough 2019 and 2020. As is the case with many industries, COVID-19 has severely affected the short– and medium-term outlook for the collaborative robot sector. In 2020 the market saw negative growth for the first time -11.3% in revenue terms, and -5.7% in shipment terms. Factory and warehouse closures slowed down demand; and customers became more cautious about investment, leading to delays or even cancellations of orders. Interact Analysis’s research indicates there will be a V-shaped rebound for the industry which will result in growth of nearly 20% in 2021, surpassing 2019 market size. Thereafter, there will be an annual growth rate of the order of 15 to 20% leading to 2028. The forecast has been lowered compared to the equivalent 2019 report. Ccompetition from small articulated and SCARA robots in industrial settings, and the slower than expected increase in collaborative robot installations in non-industrial applications. – Edited from an Interact Analysis press release by CFE Media and Technology.
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control engineering
such as cleaning shopping malls and cluttered office spaces —could also be potential applications, Gupta noted. LASER-D is an ambitious platform, aimed at achieving an autonomous option that can replicate human tasks that are repetitive, tedious and dangerous, and that also require precision. Crucial in this process is LASER-D’s vision system. The vision system, Pandey said, is based on machine learning. Traditionally, it would’ve required a lot of data to train their machine – 50,000 images or so, he said. But they had limited data. “We trained the machine on a pair of images instead,” Pandey said. “One image was of the surface prior to disinfection and the second image was of the surface postdisinfection.” This increased accuracy. The vision system helps the human operator review what the robot is seeing and allows the operator to weigh in during the process, versus only at the end. ce Avni Shah, USC Viterbi. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.
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