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Foundations of Robotics
Seminar, May 31, 2006
Time
and Place | Seminar Abstract | Speaker
Biography | Presentation Slides | Speaker
Appointments
Integrated Planning and
Control for Convex-bodied Nonholonomic Systems Using
Local Feedback Control Policies
David C. Conner
Newell Simon Hall 1507
Refreshments 4:45 pm
Talk 5:00 pm
We present a technique for controlling a
wheeled mobile robot as it moves in a cluttered environment. The method
defines a hybrid control policy that simultaneously addresses the navigation
and control problem for a convex-bodied wheeled mobile robot navigating amongst
obstacles. The technique uses parameterized continuous local feedback
control policies that ensure safe operation over local regions of the free
configuration space; each local policy is designed to respect nonholonomic constraints, bounds on velocities (inputs),
and obstacles in the environment. The hybrid control policy makes use of
a collection of these local control policies in concert with discrete planning
tools. This approach allows the system to plan, and re-plan in the face
of changing conditions, while preserving the safety and convergence guarantees
of the underlying control policies.
The first half of the presentation describes the development of the local control
policies for constrained systems. First, we define policy requirements
that all local control policies must satisfy. Next, generic policies that
meet the policy requirements are developed. These policies offer
guaranteed performance and are amenable to composition within the hybrid
control framework.
The second half of the presentation deals with discrete planning within the space
of deployed control policies. The continuous closed-loop dynamics induced
by the local policies may be represented as a graph of discrete transitions.
Two methods for planning on this graph will be discussed. Traditional AI
planning (A* and D*) can order the graph to generate a switching strategy that
solves a single navigation problem over the union of policy domains.
Experimental results using this first technique will be shown. The
second planning strategy uses model checking techniques to specify sequences of
policies that address higher level planning problems with temporal
specifications. This second approach is validated in simulation.
The presentation will give an overview of these two approaches, and
discuss the relative strengths and weaknesses of the approaches. The presentation
concludes with suggestions for possible lines of research that combine the
strengths of the two approaches, thereby making it feasible to do robust
high-level behavioral planning for the systems
subject to complex interacting constraints.
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Speaker Appointments |
For appointments, please contact David
Conner (dcconner@cmu.edu)
The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.