(Georgia Institute of Technology, 2010-05)
Teeyapan, Kasemsit; Wang, Jiuguang; Kunz, Tobias; Stilman, Mike
We present successful control strategies for dynamically
stable robots that avoid low ceilings and other vertical
obstacles in a manner similar to limbo dances. Given the parameters of the mission, including the goal and obstacle
dimensions, our method uses a sequential composition of IO-linearized
controllers and applies stochastic optimization to automatically
compute the best controller gains and references, as
well as the times for switching between the different controllers.
We demonstrate this system through numerical simulations,
validation in a physics-based simulation environment, as well
as on a novel two-wheeled platform. The results show that the
generated control strategies are successful in mission planning
for this challenging problem domain and offer significant
advantages over hand-tuned alternatives.