Xiaobo Tan
MSU Research Foundation Professor and Richard M. Hong Endowed Chair in Electrical and Computer Engineering | Michigan State University
East Lansing, MI, UNITED STATES
Expert in robotic fish, mobile sensing in aquatic environments
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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 (4)
Education/Learning
Research
Biotechnology
Computer Software
Areas of Expertise (3)
Soft Robotics
Underwater Robotics
Underwater Sensing
Accomplishments (3)
Career Award (professional)
Awarded by the National Science Foundation
Teacher-Scholar Award (professional)
Awarded by MSU
Best Mechatronics Paper Award (professional)
Awarded by the American Society of Mechanical Engineers, Dynamic Systems & Control Division
Education (3)
University of Maryland: Ph.D. 2002
Tsinghua University: M.E. 1998
Tsinghua University: B.E. 1995
Links (3)
News (5)
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.
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.
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...
MSU Floats a New Solution to Invasive Species in the Great Lakes
BTN : Big Ten News Network
2016-02-18
The mechanical maritime creatures are the brainchild of Dr. Xiaobo Tan and his team at Michigan State. They came up with the idea while looking into an affordable, efficient drone system that could monitor the Great Lakes and surrounding waterways. “When you think about Michigan, you think about the beauty and fun of the Great Lakes,” said Tan, a professor of electrical and computer engineering at Michigan State. “But it is a big, unknown world, full of risk factors such as invasive species.”
Meet this MSU Invention: Robot Fish
Michipreneur
2015-07-22
According to Tan, “The robots can carry different sensors depending on its specific mission. We’re able to control the robot to dive, swim, go to particular spots, collect data and send the data back to us.”
Journal Articles (5)
Using Control Barrier Functions to Incorporate Observability: Application to Range-Based Target Tracking
Journal of Dynamic Systems, Measurement, and Control2024 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.
Real-time invasive sea lamprey detection using machine learning classifier models on embedded systems
Neural Computing and Applications2024 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).
Label-efficient learning in agriculture: A comprehensive review
Computers and Electronics in Agriculture2023 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.
Characterization of acoustic detection efficiency using an unmanned surface vessel as a mobile receiver platform
Animal Biotelemetry2023 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.
IMU-assisted robotic structured light sensing with featureless registration under uncertainties for pipeline inspection
NDT & E International2023 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.
