Uploaded February 2024 | Updated September 2026, 3 hours ago
Maryland Robotics Center Seminar: From Sea to Space: Machine Learning for Robot Perception in the Wild
Katie Skinner
Assistant Professor of Robotics
Assistant Professor of Naval Architecture and Marine Engineering
College of Engineering
University of Michigan
Field robotics refers to the deployment of robots and autonomous systems in unstructured or dynamic environments across air, land, sea, and space. Robust sensing and perception can enable these systems to perform tasks such as long-term environmental monitoring, mapping of unexplored terrain, and safe operation in remote or hazardous environments. In recent years, deep learning has led to impressive advances in robot perception. However, state-of-the-art methods still rely on gathering large datasets with hand-annotated labels for network training. For many applications across field robotics, dynamic environmental conditions or operational challenges hinder efforts to collect and manually label large training sets that are representative of all possible environmental conditions a robot might encounter. This limits the performance and generalizability of existing learning-based approaches for robot vision in field applications.
In this talk, I will discuss unique challenges for robot perception in dynamic, unstructured, and remote environments often encountered in field robotics applications. I will present my recent research to overcome these challenges to advance perceptual capabilities of robotic systems across sea, land, and space. Lastly, I will share my insight on opportunities to integrate learning-based approaches with field robotic systems for practical deployment.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
Maryland Robotics Center Seminar: From Sea to Space: Machine Learning for Robot Perception in the Wild
Katie Skinner
Assistant Professor of Robotics
Assistant Professor of Naval Architecture and Marine Engineering
College of Engineering
University of Michigan
Field robotics refers to the deployment of robots and autonomous systems in unstructured or dynamic environments across air, land, sea, and space. Robust sensing and perception can enable these systems to perform tasks such as long-term environmental monitoring, mapping of unexplored terrain, and safe operation in remote or hazardous environments. In recent years, deep learning has led to impressive advances in robot perception. However, state-of-the-art methods still rely on gathering large datasets with hand-annotated labels for network training. For many applications across field robotics, dynamic environmental conditions or operational challenges hinder efforts to collect and manually label large training sets that are representative of all possible environmental conditions a robot might encounter. This limits the performance and generalizability of existing learning-based approaches for robot vision in field applications.
In this talk, I will discuss unique challenges for robot perception in dynamic, unstructured, and remote environments often encountered in field robotics applications. I will present my recent research to overcome these challenges to advance perceptual capabilities of robotic systems across sea, land, and space. Lastly, I will share my insight on opportunities to integrate learning-based approaches with field robotic systems for practical deployment.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
![Maryland Robotics Center Seminar, January 31, 2025: Markus P. Nemitz [REUPLOAD]](https://i.ytimg.com/vi/g1aHjIuysYI/mqdefault.jpg "Maryland Robotics Center Seminar, January 31, 2025: Markus P. Nemitz [REUPLOAD]
Maryland Robotics Center Seminar: Design. Print. Deploy. Enabling Swarm Robotics via Additive Manufacturing
Markus P. Nemitz, Ph.D.
Assistant Professor, Mechanical Engineering
Tufts University
Swarm robots offer transformative potential for applications where rapid and efficient coverage of large areas is critical. However, the high cost and fragility of advanced robots, coupled with the limited functionality of affordable alternatives, have historically hindered their large-scale deployment, confining much of swarm robotics research to simulations. While drones have successfully evolved into capable, low-cost swarm robots through commercialization, their fragility and inability to physically interact with the environment have limited their use in contact-based tasks and underwater operations. To address these challenges, our research focuses on the rapid design and fabrication of low-cost, capable, and scalable terrestrial swarm robots using additive manufacturing. In this talk, I will present strategies for creating increasingly intelligent yet affordable robots, advancing the cost-capability trade-off in robotics. I will showcase developments in 3D-printed soft quadrupeds, fluidic actuators, and controllers, exploring their current performance, future potential, and how they bridge the gap between laboratory prototypes and real-world applications. By advancing swarm engineering, we unlock new opportunities for distributed problem solving, such as explosive ordnance disposal, where expendable robots can be produced at a cost lower than the landmines they neutralize.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu")
