49 promising business case. Their aim was to provide services centred on data gathered using consumer-grade UAS, but they soon found the available systems were lacking. “We had a very clear vision for the company right from the beginning: we wanted to survey in extreme environments and generate very high-quality data, replacing helicopters in high-risk environments,” Klusak notes, lamenting: “I got back from Antarctica and realised that we were really shackled by the airframe technology.” A subsequent operation based on an icebreaker reinforced the need for more reliable equipment for operating in extreme environments, and Orthodrone concluded that they should develop its own. Klusak then ran the team’s idea past Mirko Denecke, whom he met in Antarctica while Denecke was the senior superintendent of the German Antarctica Station. “We got along really well, and it turned out that he’s an ArduPilot core developer,” Klusak says, adding that Denecke quickly joined the project. Given their previous experience, it was clear that a significant payload capacity was essential to carry the kind of heavy, survey-grade sensor systems typically mounted on helicopters, as well as a flight time of at least two hours. “We are at three hours now, with a 5 kg payload, so we’re pretty happy with that.” The team also wanted something that would withstand very harsh conditions with wind gusts of up to 20 m/sec (72 kph). “We are very clear about our market,” Klusak says. “We’re focusing on offshore.” It soon became clear that the vehicle would have to carry multiple gimbals, or a mix of gimballed and nongimballed payloads, which proved to be cumbersome, he recalls. This motivated the team to find a solution to the data-quality issues arising from having multiple sensors with different positional reference systems. “We went around that by making the drone a gimbal, because this way all the payloads are stabilised and have the same references – that loops back to our spatial data expertise.” Klusak stresses that the position and attitude references for the payloads collectively are not those used by the UAV for navigation. These are higherquality survey-grade solutions, such as Trimble Aplanix APX-20, which are rigidly connected to all the sensor systems and GNSS antennas within the payload bay, allowing for calibrated, highly accurate, multi-sensor payloads. “This is where you get superior data quality out of all these systems.” A fully stabilised fuselage makes a significant difference compared with any vehicle that carries a gimballed sensor and mounts its GNSS antennas on the fuselage, as is the convention, because the gimbal moves separately from those antennas, creating an undesirable offset. “You can compensate for that by reading out the positions of the gimbal’s motors or placing extra IMUs on different parts, so you know where each payload is pointing, and then calculate the correction,” says Klusak. “But then you’re always adding weight and complexity, and you are losing quality because each of those additions brings its own errors, and they all add up. If it’s one fixed system, you’re in a very different league. “Also, because our system is always stabilised, the antenna is always at the same spot and always pointing upright. There are no lever arms, no parts moving around and you always have the entire sensor payload sitting exactly where you want it. There is no open point in the system where the errors add up.” When a gust hits, the propulsion system moves around the fuselage, which supports the sensors, fuel storage and powertrain, correcting for pitch and roll so the sensors stay where they are, regardless of the flight direction or wind compensation. “And this really is the trick,” Klusak says. “A good example is Lidar data acquisition. Lidar data depends on really good trajectories, so you know where you were in every split second of data acquisition, otherwise it doesn’t work. “These trajectories depend very much on the position and attitude of the sensor, and then on the accuracy of how you record that attitude to compensate for the position sampling rate. Our system makes that a lot easier because the sensor attitude changes so much less, and eliminates all the little jerking motions usually associated with multirotor flight.” Pivoting the yoke and the propulsion system around the fuselage involves moving significantly less mass than Orthodrone Pivot | UVD Uncrewed Systems Technology | October/November 2024 The rotor system pivots about the vehicle’s roll axis (22) and pitch axis (6), while the fuselage, consisting of the payload section (20a) and propulsion section (20b), remains stable
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