(Georgia Institute of Technology, 2010-05)
Kolhe, Pushkar; Dantam, Neil; Stilman, Mike
This paper presents three effective manipulation
strategies for wheeled, dynamically balancing robots with articulated
links. By comparing these strategies through analysis,
simulation and robot experiments, we show that contact
placement and body posture have a significant impact on the robot's ability to accelerate and displace environment objects.
Given object geometry and friction parameters we determine
the most effective methods for utilizing wheel torque to perform
non-prehensile manipulation.
(Georgia Institute of Technology, 2010)
Dantam, Neil; Stilman, Mike
We present the Motion Grammar: a novel unified representation
for task decomposition, perception, planning, and hybrid control
that provides a computationally tractable way to control robots in
uncertain environments with guarantees on completeness and correctness.
The grammar represents a policy for the task which is
parsed in real-time based on perceptual input. Branches of the syntax
tree form the levels of a hierarchical decomposition, and the
individual robot sensor readings are given by tokens. We implement
this approach in the interactive game of Yamakuzushi on a
physical robot resulting in a system that repeatably competes with
a human opponent in sustained game-play for matches up to six
minutes.