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Disinfection robot developed to help stop COVID-19 spread, More collab- orative robots; Headlines online
Machine learning, machine vision: Robot helps stop COVID-19 spread
For robots on wheels, narrower, shallower spaces, like between desks in a classroom or on stairwells, wheels can be limiting. LASER-D (Legged Agile Smart Efficient Robot for Disinfection) is a fourlegged robot created by a team of USC researchers at the USC Viterbi School of Engineering. LASERD (Legged Agile Smart Efficient Robot for Disinfection ) a four-legged robot created by a team of USC researchers at the USC Viterbi School of Engineering. The robot combines locomotive agility and chemical disinfection to fight COVID-19, among other applications.
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“This is the first time we’ve combined a legged robot with the disinfection task,” said Quan Nguyen, an assistant professor of aerospace and mechanical engineering. This can be challenging, because we need to maintain mobility while positioning for disinfection. LASER-D conserves energy by walking and positioning its body simultaneously. Thus, we can just use the robot orientation to control the spraying of disinfectant, instead of attaching an extra arm
to perform this task,” Nguyen said. LASER-D has been tested around campus. While LASER-D is not yet autonomous, increased autonomy and increased distance between the human operator and the robot are long-term development goals. Said master’s student Abhinav Pandey, “Like a human, ‘Just two images were used for training, instead of SEE VIDEO ONLINE the system should be able to identify what has to be disinfected, whether or not the disinfection took place properly during the first round, and whether or not the using 50,000 images.’ robot should move on or perform a second round of disinfection.” These are targets of a future version. With LASER-D’s ability to move while spraying, the team believes it could be useful in different areas, including agriculture. “A robot like LASER-D could perform very localized agricultural tasks like precision pesticide dispensing or precision irrigation,” said SK Gupta, Smith International Professor of Mechanical Engineering and Computer Science. Cleaning applications that focus less on disinfection and more on aesthetics 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.
Collaborative robot market surge
Interact 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.
Headlines online
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