RSS 2011 Workshop: Integrated Planning and Control:  
 Friday Morning (July 1) - ½-day 
    Room: GFS 118


Slides from talks have been posted.  (See schedule for details).

This was done in coordination with the Comparison of Reinforcement Learning and Optimal Control Methods for Real-World Robotic Tasks workshop on Friday afternoon.   Check out their links for some interesting talks too!


Playing with dynamic robots is fun!   Making them do work, however, isn’t so easily done.

Modern systems control has to factor both the motion plan and the feedback action – for instance external obstacles and internal motor saturation.   There are several solution pathways ranging from numeric decision-policy search strategies (for which optimization is central) to optimal controls (for which system system-identification is central) to robust hardware (for which design is central).

By factoring control feasibility and parameter estimation in a unified manner, integrated planning and control methods have the best of both domains.  They can exploit control models and verification tools, yet work around external constraints and obstacles.  

The goal of this of workshop is to provide a forum for both the science and the systems:  from algorithms to tools to make this work.  It will:

  • Gather a diverse set of researchers from hardware to software to optimization;
  • Provide honest commentary on the tools of the trade; and
  • Allow for interesting positive and negative example
    (because much can be learnt from what doesn’t work). 

Posters are invited for presentation.   
Brainstorming is encouraged.  Excessive PowerPoint is discouraged.

 Key Dates

  • Abstracts/Snapshots: Tuesday, May 31, 2011
  • Acceptance: Tuesday, June 21, 2011
  • Workshop: Friday, July 1, 2011 -- Morning -- Half-day
The scope of this workshop is to gather systems, design, and controls researchers from across the world.  The goal is to move towards more agile platforms and better tools.  As such, contributions are encouraged on:
  • The science of complex systems with dynamic and environmental constraints;
  • Robot designs / technologies with extended  locomotive capabilities;
  • Best practices for system  design, implementation, and operation; and,
  • Applications to education

  • Surya Singh, ACFR, The University of Sydney  (and The Robotics Lab, The University of Queensland) 
  • Russ Tedrake, Robot Locomotion Group, MIT
  • Peter Corke, CyPhy Lab, Queensland University of Technology