Skip to main content

Robotics and Sensors Research

Researchers in the School of Science and Engineering at Saint Louis University are preparing for a future where robots can improve the way we live. From machines that change remote work to systems that make the world more accessible, the future of technology is becoming a reality in labs across campus. 

Research Projects

A human and robot are shown side-by-side replicating the other's movement.
The manipulator used in the CHROME Lab's robotics research replicates a remote user's arm motion.

Enhancing Remote Communication with Robotics

The Collaborative Haptics, Robotics and Mechatronics (CHROME) Lab, led by Jenna Gorlewicz, Ph.D., chair of the Department of Aerospace and Mechanical Engineering, includes a team of undergraduate and graduate researchers focused on bridging novel technical advancement with societal impact through projects that directly impact the community. With more than $15 million in funding support for the lab since its inception, research projects have explored how telerobots and wearable haptic devices can enhance remote communication, in addition to projects spanning technology, usability and accessibility.

Learn More About the CHROME Lab

Improving a Wheelchair User's Experience with Robotics

A student sits in a seat with a robotic arm while wearing VR glasses.

A Mecharithm Lab researcher uses a virtual reality headset to remotely control WheelArm, a wheelchair-mounted robotic arm, while collecting data for robots that understand spoken requests and ask clarifying questions.

With the goal of assisting wheelchair users with everyday tasks, the WheelArm, a project out of the Mecharithm Lab led by Madi Dian, Ph.D., an assistant professor of aerospace and mechanical engineering, is training robots to understand spoken requests and clarifying questions. Researchers use a virtual reality headset to remotely control WheelArm, a wheelchair-mounted robotic arm, while collecting data that can be used to train vision-language-action models.

Learn More About the Mecharithm Lab

Advancing Perception and Embodied Robotics

Graduate student researchers in the AIRLab work together to integrate and calibrate a custom sensing platform on an industrial robotic arm. 
Graduate student researchers in the AIRLab work together to integrate and calibrate a custom sensing platform on an industrial robotic arm. 

The AIRLab, led by Hadi Akbarpour, Ph.D., an assistant professor in the Department of Computer Science, is working to understand the physical world more reliably by combining complementary sensing technologies: Conventional cameras with emerging modalities like event-based vision and polarization imaging, machine learning, geometric computer vision and robotics.

This approach can help gather useful information in conditions where ordinary cameras struggle, like rapid motion, motion blur, strong illumination changes, reflective surfaces and scenes with limited visual texture. The team hopes to enable robots and autonomous systems to perceive complex environments more robustly, interact with their surroundings and make better-informed decisions about how to act in the real world.

Learn More About the AIRLab

Developing Brain-Controlled Hearing Aids

A mannequin head wearing headphones sits in the middle of a large circle containing small machines.
Hearing aid research out of Yan Gai's neuroengineering lab explores how users hear sound and how the experience can be improved. 

Hearing-aid users can face challenges in noisy environments with current generation hearing aids. In the neuroengineering lab of biomedical engineering associate professor, Yan Gai, Ph.D., researchers are exploring how to improve that experience.

By first studying spatial auditory attention using electroencephalography, which uses sensors to monitor activity in the brain, the team was able to explore which direction a user is focusing in on, allowing researchers to adjust their hearing-aid algorithm accordingly. From there, researchers are developing a physiologically based speech-segregation algorithm that selectively removes or attenuates unwanted sound sources. Ultimately, they're working to improve speech intelligibility for hearing-impaired listeners using robotic sensors and human-machine interface.

Related Academic Programs