Ever since robots have existed, the fear of machines crowding out humans for their jobs has persisted.
But for this research project, engineers at West Virginia University are deploying robots to help workers keep their jobs — saving them from slips, falls and potential workplace hazards.
Yu Gu and Jason Gross, associate professors in the Department of Mechanical and Aerospace Engineering, received $367,000 from the National Science Foundation to study ways to reduce fall hazards in retail environments.
To do this, Gu and Gross will use robots to delineate and detect hazards along the floor surfaces of wholesale and retail spaces.
“There is a significant slip-and-fall problem in retail spaces,” said Gross, also acting president of mechanical and aerospace engineering. “So we’re trying to find a way to use robots to provide situational awareness, monitor risk, and provide walking maps.”
Occupational injuries have plagued the wholesale and retail workforce with high incidence rates and injury counts, the researchers said. Grocery stores and pharmacies are among the sites with the highest nonfatal injury rates, they added. Each year, there are approximately 570,000 injuries among the wholesale and retail workforce.
The students working with Gu and Gross are preparing a robotic “test bed” to mimic a retail environment where the team can develop and refine their approach to how machines analyze potential hazards.
One way is to equip robots with cameras, Gu said.
“Some might say, ‘Why not use the security cameras already in stores to detect slip and fall hazards?'” Gu said. “The limitation is in appearance, which can be misleading. It is better not only to equip a robot with a camera but also to drive it on the surface to see how slippery it is. The robot’s wheels are a best estimate of the risk of slipping.
Gu and Gross set three goals for this research, carried out in collaboration with the University of Florida. The first is to identify and assess the holistic risks associated with operating robots in these work environments.
The second is to develop a new function that could increase a wide range of robots to monitor the indoor floor surface while performing primary functions, such as serving as a shopping guide. The data will generate real-time indoor walkability maps informing pedestrians of potential hazards.
Finally, the research team will investigate the effects of robots and walkability maps on worker exposure to physical fall risk, cognitive workload, and psychological impacts at these sites.
Gu said this study builds on existing research by Cagri Kilic, a postdoctoral researcher at the Statler College of Engineering and Mineral Resources in the WVU Navigation Lab. Kilic has led research on slip estimation in planetary rovers. He developed a way for extraplanetary rovers to use non-visual information to maneuver in dangerous terrain.
“Thanks to this research, we can easily estimate the slip based on the wheel-terrain interaction,” Gu said. “We can strategically spin the wheels in certain ways to better estimate wheel spin while we’re driving.”
“We have this ability, while the robot is rolling, to monitor the on-board sensors and compare the speed of the wheels against the actual speed of the robot,” Gross said. “We can infer the slip and occasionally deploy a slip meter to calibrate it.”
The team also plans to test the robots after hours in an actual retail space.
“We did this with a robot traversing a certain unique area,” Gross said, “but branching out to combine that with camera data is one of the exciting research aspects of the project.”
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