Aircraft collision avoidance is a pervasive need in this modern age of flight. We present a 2-D automated collision avoidance flight controller for automated collision avoidance amongst 2 aircraft. This controller is designed to satisfy safety and liveness requirements, implemented using Simulink and Stateflow, and verified using safety and liveness monitors.
A common problem in autonomous route planning and controls to implement efficient motor control, sensor feedback, and route planning algorithms to allow a robot to successfully navigate and traverse a line grid maze from a start point to a different destination point in an efficient manner. We present an E-Puck controller that utilized ground sensor feedback to perform a variety of functions; detect nodes (cross-sections), detect lines just past nodes, provideBraitenberg line tracking functionality, and allow for left and right turns on a line grid. In addition, we present an AStar algorithm that is utilized to efficiently solve for a route from a start node to an end node in a line grid maze. Finally, we present tuned parameters for node detection, line just passed node detection, line following, turning logic, and ground sensor threshold parameters resulting in a stable system.
Colored Petri Nets are a directed graph modeling approach utilized to reason about race conditions and deadlocks within concurrent systems. We present a Design Studio approach to develop, simulate, and analyze Colored Petri Nets. Our implementation consists of a modeling environment developed within WebGME, and a series of Python plugins for the simulation and analysis of Colored Petri Nets. The target audience for this paper and tool are for those seeking to reason about deadlocks and race conditions within concurrent systems.