Balanced and Human-like Robotic Bipedal Gait
The study of bipedal robotic gait strategy from the fundamental point of view to produce human-like gait. The project explores the dynamics of the bipedal systems and analyses it through simulations and experimental validation. This project is carried out in collaboration with Professor Oussama Khatib (Stanford University) and Professor Mary Galea (Physiotherapy). Funded by ARC Discovery (DP1093476).
In this project, we concentrated on the study of dynamic walking, with a fundamental focus on the underactuation aspect of the human gait and the engineering techniques in manipulating underactuated mechanisms. This study is fundamentally important in producing a balanced as well as energy efficient bipedal gait.
Computational Model of Human Motor Control and Motor Learning
The project aims to study the human motor behaviour in achieving force / motion control and motor learning of a new task, through the use of fundamental engineering models, especially control theory. The outcomes are applied to "Rehabilitation Robotics" project to provide a rigorous treatment to the formulation of the strategies used in the rehabilitation robotics study. This project is carried out in collaboration with external collaborators: A/Prof. Etienne Burdet (Imperial College, London) and Dr Chris Freeman (University of Southampton, UK).
Iterative Learning Control is explored in this study, combined with human-experimentation data from healthy subjects, to shed light to the mechanisms of human motor learning. The extension of the outcomes can be applied on the task of motor rehabilitation, as it has been reported in the literature that the mechanism of human motor function recovery is analogous to that of motor learning, albeit a much slower learning (recovery) rate.
At this point, the project also looks to extend the fundamental study onto a set of more challenging tasks, such as redundant manipulation and redundant motion trajectories, generalisation of established skills onto the learning of new (similar) tasks, and the accommodation of constraints in task execution.
Hybrid Cable-driven Robotic Manipulator
This project starts from the state-of-the-arts of cable-driven parallel robotic manipulator (CDPRM) and aims towards the efficient modelling, kinematics calculations, control strategy (optimisation of cable forces), and workspace analysis of multi-segment cable-driven manipulator. The current work has achieved the general case formulation of the kinematics relationship, the equations of motion and simulation of cases with large numbers of cable on N-link system.
The outcomes has been further studied for a biomechanics application where the musculoskeletal system is modelled as the cable and the rigid links of the multi-link cable driven robot. The implementation of muscle models onto the cable dynamics has been carried out and provides an early workspace estimate of a human upper limb through the hybrid cable robot model.
Leveraging on the more fundamentally oriented projects above, this project focuses on the study of robotics technology in the clinical rehabilitation of people with motion impairment, such as in post-stroke patients. This project is conducted in collaboration with Professor Mary Galea of the School of Physiotherapy and the Melbourne University Virtual Environment for Simulation (MUVES). This is an interdisciplinary project, covering various engineering sub-topics as well as clinical and communication topics. One of the sub-projects was funded by the Institute of Broadband Enabled Society (IBES) in 2010, studying the effect of network latency in the engineering systems and the clinical communication.
Magnetic Levitation (Maglev) Vehicle Optimisation
The robotics lab is also highly involved in the Melbourne School of Engineering research initiatives in Magnetic Levitation systems, through the study of mechanism design and analysis of smart mechanical suspensions, and the study of intelligent method for the electromagnetic actuation in the levitation (suspension), guidance, and propulsion of the robot.
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Department of Mechanical Engineering
Building 170, Level 1
The University of Melbourne
Parkville, VIC 3010