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.
This paper proposes criteria for the verification of behavioral designs for hardware written in VHDL. The criteria are analogous to testing criteria for software, but were adapted to the specific needs and constructs of hardware designs written in VHDL. We examine the potential value of these criteria with respect to desirable properties for evaluation criteria that were originally developed for sofrware. Then we apply the VHDL criteria to several design examples with varying complexities to demonstrate their practical usefulness. Although, applying sofmare testing techniques to hardware design at the behavioral level is not new, this work, to the best of our knowledge, is the first attempt to analyze the approach from the theoretical point of view and to lay the groundwork for achieving error-free design at the behavioral level.
This paper addresses the challenge of embedded computing resources required by future autonomous Unmanned Aircraft Systems (UAS). Based on an analysis of the required onboard functions that will lead to higher levels of autonomy, we look at most common UAS tasks to first propose a classification of UAS tasks considering categories such as flight, navigation, safety, mission and executing entities such as human, offline machine, embedded system. We then analyse how a given combination of tasks can lead to higher levels of autonomy by defining an autonomy level. We link UAS applications, the tasks required by those applications, the autonomy level and the implications on computing resources to achieve that autonomy level. We provide insights on how to define a given autonomy level for a given application based on a number of tasks. Our study relies on the state-of-the-art hardware and software implementations of the most common tasks currently used by UAS, also expected tasks according to the nature of their future missions. We conclude that current computing architectures are unlikely to meet the autonomy requirements of future UAS. Our proposed approach is based on dynamically reconfigurable hardware that offers benefits in computational performance and energy usage. We believe that UAS designers must now consider the embedded system as a masterpiece of the system.
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