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GRASP Special Seminar: Sohee Lee, Technische Universität München, "Dynamics-Based Motion Planning, Control, And Task Programming For Mobile Manipulation"
Presenter: Sohee Lee (Homepage)
Friday March 22, 2013 from 3:00pm to 4:00pm
* Alternate Location: Moore 317*
The contents are divided into three parts of: (i)
modular and reusable software architectures for motion programming;
(ii) motion control laws that take into account the limited computing
resources; (iii) online rollover prevention in high speed mobile
manipulation based on the Lie group dynamics formulation;
(i) I describe a unified framework for task planning, motion planning, and control of wheeled mobile manipulators. This relates to the setting up of a (low-level, control level) motion primitives database which is user-friendly and reusable and aims to combine with the higher level components for reasoning and intelligence, etc. As a result, the integrated, hierarchical programming environment for autonomous robots is developed.
(ii) In the literature of human motor control, it is well known that humans select the optimal motion among diverse feasible motions between initial pose and goal pose. The various optimum criteria (e.g., minimum energy, minimum jerk, minimum torque change, etc.) are evaluated to explain the theory of human motor coordination. I suggest the minimum attention that takes into account the cost of control as a paradigm for human-like movement generation of a robot.
(iiI) I briefly introduce the Lie group dynamics formulation, and as an application of this, a real-time dynamic balancing control law for wheeled mobile manipulators is proposed. For the dynamic stability criterion of zero moment point, a correct formulation which makes the definition of a potential function mathematically consistent and physically plausible is developed. Also, I derive efficient recursive algorithms for computing exact analytic gradients of the zero moment point functions. This leads to marked improvements in convergence and computational performance over existing approaches.
Sohee Lee is a postdoctoral researcher in the Intelligent Autonomous Systems Group at the Technische Universität München. She received her Ph. D. degree at the department of mechanical and aerospace engineering in 2011 from Seoul National University and worked as a postdoctoral researcher at the Humanoid Robot (HUBO) Research Center in KAIST. In Lee's graduate work, she focused on three subjects: 1) integrated, hierarchical programming environment for autonomous mobile manipulation; 2) robust rollover prevention for high speed mobile manipulation; 3) the minimum attention theory as a paradigm for human-like movement generation of humanoids. Lee worked for the project to integrate and implement a task planning, motion planning and control framework to a real robot for 4 years and participated a 'Robot Grand Challenge' contest with other groups. When she was in the Hubo lab, Lee tested her dynamic balancing algorithm for high speed mobile manipulator named HuboQ. And then, she moved to TUM and continued to research on the autonomous mobile manipulation and humanoid movement generation.