Autonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a time-triggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing the need to, based on the influence of the environment onto the drone operation. As a result, reactive control can dynamically adapt the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time.
Robot vehicle platforms, often called "drones," offer exciting new opportunities for mobile computing. While many mobile systems, such as smartphones and connected cars, simply respond to device mobility, drones allow computer systems to actively control device location. Such a feature enables interactions with the physical world to happen in new ways and with new-found scale, efficiency, or precision.4,8,18
Autopilots. Figure 1 schematically illustrates the hardware and software components in modern drone platforms. Key to their operation is the autopilot software implementing the low-level motion control. The control loop processes high-level commands coming from a Ground-Control Station (GCS) as well as various sensor inputs, such as, accelerations and Global Positioning System (GPS) coordinates, to operate actuators such as electrical motors that set the 3D orientation of the drone.
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