Planning in Robotics and Beyond - ICRA 2020

1225 views
Download
  • Share

The past two decades have witnessed incredible advances towards the design of autonomous systems. This talk will discuss the role of motion planning in yielding solutions for an agent that is able to execute a variety of tasks in a variety of settings. Problem decomposition has been and remains a difficult task, and motion planning algorithms are today exploited for this purpose. Another critical step is to produce motion from high-level specifications. The specifications declare what the robot must do, rather than how the task is to be done. In that realm, motion planning principles guide the development of new frameworks that integrate advances in logical reasoning and program synthesis. The talk will also illustrate how the experience and insight gained from motion planning are applied to computational structural biology and, in particular, to the design of new therapeutics.


Lydia E. Kavraki is the Noah Harding Professor of Computer Science and Bioengineering at Rice University. She obtained her B.A. from the University of Crete in Greece and her Ph.D. from Stanford University. She is the Director of the Ken Kennedy Institute at Rice University. Kavraki also leads the NIH/NLM Training Program in Biomedical Informatics under the auspices of the Gulf Coast Consortia in Houston. Her interests are in physical algorithms and their applications in robotics and medicine. Kavraki is the recipient of the ACM Grace Murray Hopper Award, the ACM Athena Award, and the ACM-AAAI Allen Newell Award. She is a Fellow of ACM, IEEE, AAAS, AAAI, AIMBE, and a member of the National Academy of Medicine. Her work can be found in wwww.kavrakilab.org

The past two decades have witnessed incredible advances towards the design of autonomous systems. This talk will discuss the role of motion planning in yielding solutions for an agent that is able to execute a variety of tasks in a variety of settings. Problem decomposition has been and remains a difficult task, and motion planning algorithms are today exploited for this purpose. Another critical step is to produce motion from high-level specifications. The specifications declare what the robot must do, rather than how the task is to be done. In that realm, motion planning principles guide the development of new frameworks that integrate advances in logical reasoning and program synthesis. The talk will also illustrate how the experience and insight gained from motion planning are applied to computational structural biology and, in particular, to the design of new therapeutics.

Advertisment

Advertisment