We have conceived a novel compound multicopter (helicopter type utilizing multiple different size propellers for separate lift and attitude control) configuration specifically for flight through narrow corridors. Its design combines the contradictory requirements of limited width, high agility and long endurance while carrying a significant payload. This *Research supported by Kulab (Propolis) and KULeuven (FWO-project 6.0404.10).
Nowadays, complex image processing algorithms are a necessity to make UAVs more autonomous. Currently, the processing of images of the on-board camera is often performed on a ground station, thus severely limiting the operating range. On-board processing has numerous advantages, however determining a good trade-off between speed, power consumption and weight of a specific hardware platform for onboard processing is hard. Many hardware platforms exist, and finding the most suited one for a specific vision algorithm is difficult. We present a framework that automatically determines the most-suited hardware platform given an arbitrary complex vision algorithm. Our framework estimates the speed, power consumption and flight time of this algorithm for multiple hardware platforms on a specific UAV. We demonstrate this methodology on two real-life cases and give an overview of the present top processing CPU-based platforms for on-board UAV image processing.
Multicopters are the most popular rotary type of unmanned aerial vehicles. They are a type of helicopter with three or more, usually fixed-pitch, propellers that lift and control the platform by individually changing their rotational velocities. The main advantages of a multicopter are its compactness, robustness, and low cost to build and repair. However, currently no published research determines objectively, quantitatively, and experimentally, the maneuverability and agility of multicopters. Numerous maneuverability and agility metrics, together with detailed test procedures and minimum requirements, exist for manned aircraft. Nevertheless, some of these are not directly applicable to small-size unmanned aircraft. A new test procedure, derived from manned aircraft industry practices and research, based on a simple openloop step input maneuver, was developed. It experimentally determines nine maneuverability and agility metrics using only onboard flight controller logs. The test procedure is validated using two different multicopters.
Semi-) autonomous complex UAV missions, such as inspection or search-and-rescue in uncertain dynamic environments, require obstacle avoidance and operator shared control. Combining humans' cognitive abilities with fast automation is the key for such missions. This paper presents a flight control system architecture based on the instantaneous Task Specification using Constraints (iTaSC) methodology and software framework. iTaSC is a flexible constraint-based programming approach that generates a robot motion at runtime which automatically derives the input for a low-level controller taking into account constraints and intentions from the operator, obstacles and mission constraints. This setup is experimentally validated by navigating a multirotor UAV safely through a GPS-denied corridor using (intuitive) shared control with a pilot. In addition to the pilot's commands, automatic obstacle avoidance and object tracking are performed real-time through various onboard sensors and with limited onboard computational power.
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