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

View more experts managed by Michigan State University

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

Career Award

Awarded by the National Science Foundation

Teacher-Scholar Award

Awarded by MSU

Best Mechatronics Paper Award

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

Education

University of Maryland

Ph.D.

2002

Tsinghua University

M.E.

1998

Tsinghua University

B.E.

1995

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.

View More

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.

View More

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...

View More

Show All +

Journal Articles

Using Control Barrier Functions to Incorporate Observability: Application to Range-Based Target Tracking

Journal of Dynamic Systems, Measurement, and Control

2024

In many nonlinear systems, the observability of the system is dependent on its state and control input. Thus, incorporating observability into a control scheme can enhance an observer's ability to recover accurate estimates of unmeasured states, minimize estimation error, and ultimately, allow the original control objective to be achieved. The accommodation of observability, however, may conflict with the original control goal at times. In this paper, we propose the use of control barrier functions (CBFs) to enforce observability and thereby facilitate the convergence of the state estimate to the true state while accommodating the original control objectives.

View more

Real-time invasive sea lamprey detection using machine learning classifier models on embedded systems

Neural Computing and Applications

2024

Invasive sea lamprey (Petromyzon marinus) has historically inflicted considerable economic and ecological damage in the Great Lakes and continues to be a major threat. Accurately monitoring sea lampreys are critical to enabling the deployment of more targeted and effective control measures to minimize the impact associated with this species. This paper presents the first stand-alone system for real-time detection of sea lamprey attachment on underwater surfaces through the use of classifier models deployed on a microcontroller system. A range of low-complexity models was explored: single-layer artificial neural networks, logistic regression, Gaussian Naive-Bayes, decision trees, random forest, and Scalable, Efficient, and Fast classifieR (SEFR).

View more

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.

View more

Show All +