A Contract Based Approach to Collision Avoidance for UAVs

In this work, a contract-based reasoning approach is developed for obstacle avoidance in unmanned aerial vehicles
(UAV’s) under evolving subsystem performance. This approach is built on an assume-guarantee framework, where
each subsystem (guidance, navigation, control and the environment) assumes a certain level of performance from
other subsystems and in turn provides a guarantee of its own performance. The assume-guarantee construct then
assures the performance of the overall system (in this case, safe obstacle avoidance). The implementation of the
assume-guarantee framework is done through a set of contracts that are encoded into the guidance subsystem, in the
form of a set of inequality constraints in the trajectory planner. The inequalities encode the relationships between
subsystem performance and operational limits that ensure safe and robust operation as the performance of the control
and navigation subsystems and environment evolve over time. The contract inequalities can be obtained analytically
or numerically using an optimization based path planner and UAV simulation. The methodology is evaluated in the
context of head-on obstacle avoidance, where the contracts are constructed in terms of (1) minimum obstacle detection
range, (2) expected obstacle size, (3) maximum allowed cruise velocity, (4) maximum allowable thrust, roll and pitch
angles, and (5) inner-loop tracking performance. Numerical and analytical generation of these contracts for this
scenario is demonstrated. Finally, in-flight contract enforcement is illustrated for typical scenarios.