Xiaobo Tan

MSU Research Foundation Professor and Richard M. Hong Endowed Chair in Electrical and Computer Engineering Michigan State University

  • East Lansing MI

Expert in robotic fish, mobile sensing in aquatic environments

Contact

Michigan State University

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Biography

Electroactive polymer sensors and actuators, biomimetic robotic fish, mobile sensing in aquatic environments, control of autonomous robotic swarms, modeling and control of hysteresis, embedded control systems.

Industry Expertise

Education/Learning
Research
Biotechnology
Computer Software

Areas of Expertise

Soft Robotics
Underwater Robotics
Underwater Sensing

Accomplishments

Best Mechatronics Paper Award

Awarded by the American Society of Mechanical Engineers, Dynamic Systems & Control Division

Teacher-Scholar Award

Awarded by MSU

Career Award

Awarded by the National Science Foundation

Education

Tsinghua University

B.E.

1995

Tsinghua University

M.E.

1998

University of Maryland

Ph.D.

2002

News

MSU leads project hailed as ‘Holy Grail’ of invasive species control

MSU Today  online

2024-07-31

A project of this magnitude could only be accomplished through collaboration, said Tan, who is also director of the Smart Microsystems Lab in the College of Engineering’s Department of Electrical and Computer Engineering. Tan is known worldwide for developing a robotic fish, and while he’s an expert in his field, he couldn’t have approached this project without collaborating with researchers in other disciplines, he said.

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MSU: More trained leaders needed to solve global water crisis

MSU Today  online

2023-09-22

“We are surrounded by water crises, from the Flint water crisis; the years-long unsafe drinking water in Jackson, Mississippi; widespread contamination of water with per- and polyfluoroalkyl substances, or PFAS; and prolonged drought followed by extreme flooding in California,” said Xiaobo Tan, principal investigator, MSU Research Foundation Professor and Richard M. Hong Endowed Chair in the MSU College of Engineering.

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To Track Down Bloodsucking Lampreys, This Robot Swims Like a Fish

Vice Motherboard  

2016-10-26

GRACE is the brainchild of Dr. Xiaobo Tan of Michigan State University, and he's thinking seriously about developing a powerful, multi-user platform. "We're not just trying to publish a paper," said Dr. Tan, "we want to make something really functional." GRACE's tracking system is built on a standardized acoustic monitoring protocol that is used throughout the Great Lakes, as well as many other marine and freshwater systems to track everything from salmon to bull sharks...

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Journal Articles

IMU-assisted robotic structured light sensing with featureless registration under uncertainties for pipeline inspection

NDT & E International

2023

Laser profilometry and structured light sensors are being increasingly deployed for pipeline inspection as they provide the operator with a precise 3D map that can enable visual detection and direct insight into the integrity of the pipe. The focus of the presented paper is the design of an integrated robotic structured light sensing system used to improve the performance of 3D defect reconstruction for pipeline inspection while accommodating the uncertainty seen in a real-world environment. Point cloud registration of the consecutive 3D frames is a key factor in building this 3D map; therefore, a comprehensive featureless registration approach is proposed first, which is proven more efficient than conventional feature-based registration algorithms.

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Characterization of acoustic detection efficiency using an unmanned surface vessel as a mobile receiver platform

Animal Biotelemetry

2023

Studies involving acoustic telemetry typically use stationary acoustic receivers arranged in an array or grid. Unmanned surface vehicle (USV)-based mobile receivers offer advantages over the latter approach: the USV can be programmed to autonomously carry a receiver to and from target locations, more readily adapting to a survey’s spatial scope and scale. This work examines the acoustic detection performance of a low-cost USV developed as a flexible sensing platform. The USV was fitted with an acoustic receiver and operated over multiple waypoints set at increasing distances from the transmitter in two modes: drifting and station-keeping.

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Label-efficient learning in agriculture: A comprehensive review

Computers and Electronics in Agriculture

2023

The past decade has witnessed many great successes of machine learning (ML) and deep learning (DL) applications in agricultural systems, including weed control, plant disease diagnosis, agricultural robotics, and precision livestock management. However, a notable limitation of these ML/DL models lies in their reliance on large-scale labeled datasets for training, with their performance closely tied to the quantity and quality of available labeled data. The process of collecting, processing, and labeling such datasets is both expensive and time-consuming, primarily due to escalating labor costs. This challenge has sparked substantial interest among researchers and practitioners in the development of label-efficient ML/DL methods tailored for agricultural applications.

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