Jonathan Kok

FPGA Implementation of an Evolutionary Algorithm for Autonomous Unmanned Aerial Vehicle On-Board Path Planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application-specific evolutionary algorithm (EA) implemented entirely on a field-programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, makes it an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and 3-D terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment, and mission profiles. The architecture has been successfully synthesized for a target Xilinx Virtex-4 FPGA platform with 32% logic slice utilization. Results obtained from case studies for a small UAV helicopter with environment derived from light-detection and ranging data verify the effectiveness of the proposed FPGA-based pathplanner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

An Automated Emergency Landing System for Fixed-Wing Aircraft: Planning and Control

A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure, and aircraft. To date, few field-demonstrated systems have been presented that show online replanning and repeatability from failure to touchdown. This paper presents the development of the guidance, navigation, and control GNC component of an automated emergency landing system AELS intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing unmanned aerial vehicle UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories, and a simplified control system executes the required maneuvers to guide the aircraft toward touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial, and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and replans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.