Demo

Jarrett Holtz, Arjun Guha, Joydeep Biswas

Abstract: Complex robot behaviors are often structured as state machines, where states encapsulate actions and a transition function switches between states. Since transitions depend on physical parameters, when the environment changes, a roboticist has to painstakingly readjust the parameters to work in the new environment. In this demo we present Interactive SMT-based Robot Transition Repair (SRTR): instead of manually adjusting parameters, we ask users to identify a few instances where the robot is in a wrong state and what the right state should be. A lightweight automated analysis of the transition function's source code then 1) identifies adjustable parameters, 2) converts the transition function into a system of logical constraints, and 3) formulates the constraints and user-supplied corrections as a MaxSMT problem that yields adjustments to parameter values. This demo uses a simulated RoboCup Small Size League platform, allows users to correct faulty behaviors, and then uses SRTR to adjust parameters automatically.