Pint of Robotics: Junlei Hu, Dr. Linyan Han (PhD), and Dr. Orla Gilson (PhD)

Speaker 1: Junlei Hu(STORM Lab, IRASS, School of Electronic and Electrical Engineering, University of Leeds)

Title: Autonomous robotic manipulation on soft human tissue in laparoscopic surgery 

Bio: Junlei Hu obtained his bachelor's and master’s degree in mechanical engineering from Shanghai Jiao Tong University in 2017 and 2020 respectively. He is currently doing his Ph.D. studies under the supervision of Dr Pietro Valdastri from University of Leeds. His research interests include surgical robot, robotic planning, and computer vision.

Abstract: Robotic manipulation of 3D soft objects remains challenging in the industrial and medical fields. Various methods based on mechanical modelling, data-driven approaches or explicit feature tracking have been proposed. A unifying disadvantage of these methods is the high computational cost of simultaneous imaging processing, identification of mechanical properties, and motion planning, leading to a need for less computationally intensive methods. We propose a method for autonomous robotic manipulation with 3D surface feedback to solve these issues. First, we produce a deformation model of the manipulated object, which estimates the robots’ movements by monitoring the displacement of surface points surrounding the manipulators. Then, we develop a 6-degree-of-freedom velocity controller to manipulate the grasped object to achieve a desired shape. We validate our approach through comparative simulations with existing methods and experiments using phantom and cadaveric soft tissues with the da Vinci Research Kit. The results demonstrate the robustness of the technique to occlusions and various materials. Compared to state-of-the-art linear and data-driven methods, our approach is more precise by 46.5% and 15.9% and saves 55.2% and 25.7% manipulation time, respectively. 

Speaker 2:  Dr. Linyan Han (PhD), (Real Robotics Lab, School of Mechanical Engineering, University of Leeds)

Title: Model-based interaction force estimation and position tracking control for robotic manipulators

Bio: Linyan Han received her Ph.D. degree in Control Science and Engineering from the School of Automation, Southeast University in 2022. She is currently a postdoctoral researcher at the School of Mechanical Engineering, University of Leeds. Her interests include visual servoing, force control, position control, optimal control, nonlinear control theory and their applications to robotic systems.

Abstract: Robot manipulators need to contact with external environments properly and thus careful treatment of interaction forces is vital. In force-sensitive scenarios, traditional approaches on position control are prone to impose strong stiffness using large control gains and consequently the risk of breaking robots and harming environments becomes high. Tracking control is fundamental to robotics, serving a wide range of civil and defence applications. However, the robotic system always encounters various uncertainties and disturbances, which may negatively affect the realization of high-speed and high-accuracy position tracking control. We have developed a systematic control framework for mechatronic systems. It makes up of nonlinear modelling, disturbance estimation and compensation and advanced feedback control. The general idea can be described as follows: For the nonlinearities, system identification technology is developed to have an accurate cancellation control of them. For disturbances, they are estimated by disturbance observers and feedforward compensated. For the unmodeled nonlinearities and inestimable disturbances, the nonlinear feedback domination design is adopted to suppress them. Especially, the non-smooth feedback controller is introduced to handle both large and small error conditions. Finally, a composite control framework is formulated. To validate the effectiveness and feasibility of the proposed tracking control approach, extensive evaluations are conducted on a six-degree-of-freedom (6-DoF) manipulator.

Mentor: Dr. Orla Gilson (PhD), (School of Electronic and Electrical Engineering, University of Leeds)

Bio: Orla Gilson (PhD in Medical Robotics) is a lecturer in Mechatronics and Robotics Engineering. Having been at the University for over 10 years now, she can offer a unique insight into the journey from undergrad to academic, from learning the course to teaching it. With a passion for teaching, she has introduced all ages of students to engineering, from primary school to university. With more Q&A sessions under her belt than she can count, she can answer almost any question about the journey into academia that you can think of.