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Laura Ray

Myron Tribus Professor of Engineering Innovation

Senior Associate Dean, Faculty Development

+1 (603) 646-1243

laura.e.ray@dartmouth.edu

Professor Ray's NASA and NSF-funded research includes developing autonomous robots to study remote polar regions.

Research Interests

System dynamics and controls; robotics; signal processing; machine intelligence

Education

BSE, Mechanical and Aerospace Engineering, Princeton University 1984
MSE, Mechanical Engineering, Stanford University 1985
PhD, Mechanical and Aerospace Engineering, Princeton University 1991

Awards

Outstanding Service Award for Faculty, Dartmouth Engineering (2022)
Senior Member, National Academy of Inventors (2020)
Dartmouth Technology Innovation and Commercialization Award (2019)
American Society for Non-destructive Testing Fellowship (2001)
Ralph R. Teetor Educational Award, SAE (1997)

Professional Activities

Member, American Society of Mechanical Engineers
Member, Institute of Electrical and Electronics Engineers

Research Projects

Acoustics and signal processing

Acoustics and signal processing

Acoustics and signal processing research focuses on active noise control and distributed sensing. Active noise control reduces noise in hearing protection and communication systems to reduce noise induced hearing loss and to enhance the ability to communicate. Distributed sensing research uses signal processing to focus listening in a specified direction. This research blends mechatronics—the design of mechanical and electrical systems—with high performance signal processing and control algorithms to improve communication in noisy environments.
Robot design and smart navigation

Robot design and smart navigation

Robot design and smart navigation focuses on developing affordable robot designs that employ "smart navigation" for path planning and mobility in extreme terrain, rather than complex and expensive vision systems. We are developing solar-powered robotic platforms for deploying scientific instrumentation over hundreds of kilometers in Arctic and Antarctic regions. These robots employ proprioceptive sensors to determine whether difficult terrain is passable, and if not, to navigate around such terrain.
Terrain identification

Terrain identification

Terrain identification research focuses on using small, lightweight robots to classify, characterize, and identify terrain properties necessary to predict mobility of these vehicles on the terrain. Terramechanics models for heavy vehicles are well understood, but similar comprehensive models do not exist for lightweight (sub-500 kg) vehicles. We are developing terrain models and modeling tools that can be used to asses mobility on a given terrain, while avoiding maneuvers that cause immobilization. We seek to integrate terrain identification and traction/stability control of the robots in order to allow autonomous or remote control of these robots at the maximum attainable speeds and accelerations achievable on the terrain.
Cooperative control of multi-robot systems

Cooperative control of multi-robot systems

Cooperative control of multi-robot systems focuses on modeling and control of groups of high-speed mobile robots while accommodating communication latencies and nonlinear vehicle dynamics. In distributed cooperative control, robots communicate information about their state to each other; communication latencies and error depends on the amount of information communicated and the number of robots. We are developing distributed control system modeling and design tools that seek to maximize control bandwidth for a given information set. These tools will also assist in assessing the value of information transmitted in maintaining stability and performance of group dynamics. Both potential function path planning and control and predictive control methods are being developed.

Selected Publications

Laura Ray, Madeleine Jordan**, Steven A Arcone, Lynn M Kaluzienski, Benjamin Walker*, Peter Ortquist Koons, James Lever, Gordon Hamilton, Velocity Field of the McMurdo Shear Zone (MSZ) from Annual Ground Penetrating Radar Imaging and Crevasse Matching, Cold Regions Science and Technology 103023, 2020.
J.T. Cook*, L. Ray, & J. H. Lever, Mobility Enhancement of Heavy-Duty Tracked Vehicles Under Load Using Real-Time Terrain Characterization, Traction Control, and a Towing Winch. ASME Journal of Dynamic Systems, Measurement, and Control. 141(7), July 2019. doi: 10.1115/1.4043111
J.T. Cook*, L.R. Ray, and J. H. Lever. Dynamics modeling and robotic-assist, leader-follower control of tractor convoys. Journal of Terramechanics, 75, 57-72, Feb 2018. https://doi.org/10.1016/j.jterra.2017.05.002
Jerald D. Kralik, Tao Mao, Zhao Cheng, and Laura E. Ray, Modeling Incubation and Restructuring for Robotic Creative Problem Solving, Journal of Robotics and Autonomous Systems, special issue on Robotics and Creativity, 86, 1–12, Dec 2016.
S.A. Arcone, J.H. Lever, J., L. Ray, G. Hamilton, B. Walker* P. Koons, Ground-Penetrating Radar Profiles of the McMurdo Shear Zone, Antarctica Acquired with an Unmanned Rover: Interpretation of Crevasses, Fractures and Folds within Firn and Marine Ice, Geophysics, 81(1), Jan 2016.