Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Learning barrier functions with memory for
robust safe navigation
K. Long, C. Qian, J. Cortés, N. Atanasov
IEEE Robotics and Automation Letters 6 (3) (2021), 4931-4938
Abstract
Control barrier functions are widely used to enforce
safety properties in robot motion planning and control. However, the problem of constructing barrier
functions online and synthesizing safe controllers that
can deal with the associated uncertainty has received
little attention. This paper investigates safe
navigation in unknown environments, using onboard range
sensing to construct control barrier functions
online. To represent different objects in the
environment, we use the distance measurements to train
neural network approximations of the signed distance
functions incrementally with replay memory. This allows
us to formulate a novel robust control barrier safety
constraint which takes into account the error in the
estimated distance fields and its gradient. Our
formulation leads to a second-order cone program,
enabling safe and stable control synthesis in a priori
unknown environments.
pdf
Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
Skype id:
jorgilliyo