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

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

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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BTN LiveBIG: 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.”

The robotic fish are equipped with tracking software, allowing them to home in on their radio-tagged, flesh-and-blood brethren. And they can work in tandem to increase effectiveness...

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Meet this MSU Invention: Robot Fish

Michipreneur  

2015-07-22

Xiaobo Tan, a professor in Michigan State University’s Department of Computer Science and Engineering, is working with Guoliang Xing, also from the Department of Electrical and Computer Engineering; Charles Krueger, Department of Fisheries and Wildlife and Center for Systems Integration and Sustainability; Chris Holbrook, Research Ecologist; and Darryl Hondorp, Supervisory Fishery Biologist, Great Lakes Science Center on this long-term project. Their goal is to not only track live fish but also to detect both toxins and invasive species in lakes and rivers. The technology also allows for the testing of water quality.

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.”

He continues, “We’d been working on tracking fish in the Great Lakes with stationary equipment. In our discussions, we talked about the possibility of using technology that would allow us to create equipment that could move through the water, not just stay in one place. These discussions led to the creation of prototypes, and we are continuing to work on designing, developing and using ever more sophisticated models.”...

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Journal Articles

Design optimization of an artificial lateral line system incorporating flow and sensor uncertainties

Engineering Optimization

2017

An artificial lateral line (ALL) system consists of a set of flow sensors around a fish-like body. An ALL system aims to identify surrounding moving objects, a common example of which is a vibrating sphere, called a dipole. Accurate identification of a vibrating dipole is a challenging task because of the presence of different types of uncertainty in measurements or in the underlying flow model. Proper selection of design parameters of the ALL system, including the shape, size, number and location of the sensors, can highly influence the identification accuracy. This study aims to find such an optimum design by developing a specialized bi-level optimization methodology. It identifies and simulates different sources of uncertainty in the problem formulation. A parametric fitness function addresses computational and practical goals and encompasses the effect of different sources of uncertainty. It can also analyse the trade-off between localization accuracy and the number of sensors. Comparison of the results for different extents of uncertainty reveals that the optimized design strongly depends on the amount of uncertainty as well as the number of sensors. Consequently, these factors must be considered in the design of an ALL system. Another highlight of the proposed bi-level optimization methodolo

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Modeling of biomimetic robotic fish propelled by an ionic polymer–metal composite caudal fin

IEEE/ASME Transactions on Mechatronics

2010

In this paper, a physics-based model is proposed for a biomimetic robotic fish propelled by an ionic polymer-metal composite (IPMC) actuator. Inspired by the biological fin structure, a passive plastic fin is further attached to the IPMC beam. The model incorporates both IPMC actuation dynamics and the hydrodynamics, and predicts the steady-state cruising speed of the robot under a given periodic actuation voltage. The interactions between the plastic fin and the IPMC actuator are also captured in the model. Experimental results have shown that the proposed model is able to predict the motion of robotic fish for different tail dimensions. Since most of the model parameters are expressed in terms of fundamental physical properties and geometric dimensions, the model is expected to be instrumental in optimal design of the robotic fish.

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A control-oriented and physics-based model for ionic polymer--metal composite actuators'

IEEE/ASME Transactions on Mechatronics

2008

Ionic polymer-metal composite (IPMC) actuators have promising applications in biomimetic robotics, biomedical devices, and micro/nanomanipulation. In this paper, a physics- based model is developed for IPMC actuators, which is amenable to model reduction and control design. The model is represented as an infinite-dimensional transfer function relating the bending displacement to the applied voltage. It is obtained by exactly solving the governing partial differential equation in the Laplace domain for the actuation dynamics, where the effect of the distributed surface resistance is incorporated. The model is expressed in terms of fundamental material parameters and actuator dimensions, and is thus, geometrically scalable. To illustrate the utility of the model in controller design, an Hinfin controller is designed based on the reduced model and applied to tracking control. Experimental results are presented to validate the proposed model and its effectiveness in real-time control design.

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