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https://www.syracuse.edu/stories/zhenyu-gan-robots-engineering-computer-science/

Gan oversees the Dynamic Locomotion and Robotics (DLAR) Lab, where he builds simplistic models for legged locomotion. The lab is part of the University’s galvanic response to the rise of autonomous systems. Recent additions include the Autonomous Systems Policy Institute and the Artificial Intelligence, Autonomous Systems and Human-Technology Frontier research group.

Gan’s research draws on science, engineering and technology. Using motion-capture data to isolate the movements of animals (mainly dogs and horses), his team develops simple spring-mass models. These models imitate different gait patterns, producing locomotion through a sequence of foot contacts with the ground.

Abstract: precise trajectory tracking for legged robots can be challenging due to their high degrees of freedom, unmodeled nonlinear dynamics, or random disturbances from the environment. A commonly adopted solution to overcome these challenges is to use optimization-based algorithms and approximate the system with a simplified, reduced-order model. Additionally, deep neural networks are becoming a more promising option for achieving agile and robust legged locomotion. These approaches, however, either require large amounts of onboard calculations or the collection of millions of data points from a single robot. To address these problems and improve tracking performance, this paper proposes a method based on iterative learning control. This method lets a robot learn from its own mistakes by exploiting the repetitive nature of legged locomotion within only a few trials. Then, a torque library is created as a lookup table so that the robot does not need to repeat calculations or learn the same skill over and over again. This process resembles how animals learn their muscle memories in nature. The proposed method is tested on the A1 robot in a simulated environment, and it allows the robot to pronk at different speeds while precisely following the reference trajectories without heavy calculations.

https://arxiv.org/abs/2211.11922

Our lab collaborated with Technology Alliance of Central New York (TACNY) and rolled out the first summer program for students entering 6th-9th grades, STEM Trekkers in 2022. The program is free and open to any student with interest in science, technology, engineering, and math. We offer a comprehensive, unique, and rigorous STEM interactive educational experience that piques students’ interest in STEM and seek to highlight the crossover between industry and education in our community.

The theme for 2022 workshop was Robotics Engineering, Design and Coding. 40 students attended the workshop and they were given 20 quadrupedal robot kits (Bittle from Petoi). During the two-day workshop at SU, they learned how to design a robot, build the robot, program the robot using a graphical interface called TinkerGen, and control the robot to shake head, to walk in different directions. We also had a soccer competition on the 2nd day to let the students test and compete with their robots.

Addtionally, they had a tour to our lab at SU and the local robotic company Ramboll Inc. located in Liverpool, NY. The workshop was a great success this year and we plan to hold this program again next year. Please contact us through TACNY’s website if you want to sign up for the event of next year. https://www.tacny.org/trekkers/

Dr. Gan was invited to give a talk at ME Graduate Seminar in Worcester Polytechnic Institute on exploring passive dynamics in legged locomotion.

We got two new robots A1 and Aliengo from Unitree Robotics. We will be working on the bounding and pronking controller design for these platforms.