Reducing injuries in collaborative human-robot workspaces
Collaborative robots, also known as cobots, are growing in popularity. Factories around the world have installed more than 2 million in the last three years, and more are likely on the way, as they help reduce human injuries related to repetitive movements.
With progress, though, can come consequences: heavier and faster robots working in the same environment as people has led to new hazards.
To make these environments safer, researchers working under the direction of Heejin Jeong, an assistant professor of industrial engineering, are investigating new ways to keep people out of harm’s way.
The team members are housed in Jeong’s Human-in-Mind Engineering Research Lab. Their work garnered attention recently when research assistant Mustafa Mohammed won first place in a student elevator-pitch competition at the ACM/IEEE International Conference on Human-Robot Interaction.
In the competition, students had 30 seconds to summarize their research topic and its importance to three judges, who scored each participant on motivation, clarity, feasibility, broader impact, and timing.
Mohammed, an undergraduate neuroscience student, based his pitch on a research paper he wrote for the conference titled “Human-Robot Collision Avoidance Scheme for Industrial Settings Based on Injury Classification.”
He described his research this way: “My goal is to develop a real-time, depth-sensing surveillance method to be used in factories that require human operators to complete tasks alongside collaborative robots.”
Generally, robots perform collision detection and analysis using extra attached sensors that detect torque or current. This adds extra data and more lag time.
Mohammed’s work takes a different approach, using “3D computer vision models to calculate the distance between humans and robots from depth maps,” he said. “By not having to deal with any potential delay associated with extra sensor-based data, I predict that the likelihood and severity of collaborative robot injuries will decrease.”
The conference Mohammed and his fellow researchers attended provides an opportunity for researchers from around the world to present their best work and exchange ideas about the theory, technology, data, and science furthering the state-of-the-art in human-robot interaction. It showcases the best interdisciplinary and multidisciplinary research from communities that include robotics, artificial intelligence, human-computer interaction, human factors, design, and social and behavioral sciences.
“Mustafa is one of the most motivated and dedicated students,” said Jeong, Mohammed’s mentor and research advisor. “Since he joined my lab last summer in 2020, he has continuously worked hard, diligently, independently, and professionally.”
In addition to the conference award, Mohammed received a UIC Honors College Undergraduate Research Grant this month.
Human-Robot Collision Avoidance Scheme for Industrial Settings Heading link
Overview of Mohammed’s work with MIE Assistant Professor Heejin Jeong in the Human-in-Mind Engineering Research Lab at UIC.