Expanding Reasearch Partnerships Webinar Series

Expanding Research Partnerships Webinar Series logo 2019

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Presentation Date: April 10, 2019

Looking to the Future: Occupational Robotics Safety and Health Research at NIOSH
Juliann Scholl, PhD

Dawn Castillo, MPH  – NIOSH

NIOSH established a virtual Center for Occupational Robotics Research in late 2017 to proactively address rapidly advancing robotics technology. While robots have been used in manufacturing settings for decades, human workers have been kept away from operating robots by physical and engineering barriers. New types of robots are being designed to work alongside, move amongst, and even be worn by workers. These new types of robots are also being introduced to non-manufacturing work settings, such as agriculture, construction, and mining. While robots have potential benefits for safety and productivity, there are also safety concerns. This presentation will provide an overview of trends in robotics technologies and implications for worker safety and health, introduce the new NIOSH Center for Occupational Robotics Research and describe research needs identified by the Center. It will also provide information on new intramural research projects.

Potential Ergonomic Benefits of Personal Collaborative Robots in Strawberry Harvesting

Fadi Fathallah, PhD – University of California, Davis

California is the nation’s leading producer of strawberries, but strawberry harvesting is a very labor-intensive task that results in many workers suffering from musculoskeletal disorders, especially low back disorders (LBDs). The industry needs a means of controlling LBDs among strawberry workers, while maintaining acceptable productivity levels.  Recently, the industry has developed various strawberry harvest-aids to increase productivity. These range from commercial 15-person and 5-9 person machines, to research prototypes, such as 2-person harvest machines and single-person programmable collaborative robots. However, there are limited formal ergonomic and biomechanical studies on any of these newly introduced machines to investigate the coupling between harvest efficiency and the effects on the musculoskeletal system. This presentation will give a quick overview of the commercial strawberry harvest aids machines and describe current research on the development and evolution of personal collaborative robots and their potential role in reducing LBDs during strawberry harvesting.

Probabilistic Posture Modeling Enhances the Ergonomics and Safety of Human-Robot Collaborations

Andrew Merryweather, PhD – University of Utah

The way we work and interact with our workplace environment and coworkers is evolving rapidly with new robotics technologies. As a result, ergonomics and human factors must be innovative in order to meet emerging challenges. We can use wearable sensors, robotics and musculoskeletal models to enable greater knowledge of exposure, injury risk and prevention. One significant challenge is defining the postural relationship between humans and robots during human-robot interactions (HRI). This presentation will highlight examples of human intention recognition and posture modeling during physical HRI. Robots need to be able to learn, predict and recognize a human’s intention to perform a task, often adapting their motion based on the human’s movement. When a human interacts with a haptic device to perform a task, we can use the robot to estimate human posture and move in a way that optimizes ergonomics. For example, a surgeon using a surgical robot may need to apply a force to remove tissue and then perform suturing. While the surgeon is manipulating a haptic input device, the robot can determine the surgeon’s posture and move toward a better posture for the surgeon.
Probabilistic modeling and learning algorithms that consider human biomechanics can be used in this area and have the ability to predict human motion in future steps to minimize risk of future musculoskeletal injuries. Collaborative research between the Ergonomics and Safety Lab and the Utah Learning Lab for Manipulation Autonomy (LL4MA) at the University of Utah is defining new methods to use computer science and ergonomics to enhance human safety and efficiency during HRI.

Page last reviewed: March 12, 2019