Abstract
Unmanned Aerial Vehicles (UAVs) with acceptable performance are becoming commercially available at an affordable cost. Due to this, the use of drones for real-time data collection is becoming common practice by individual practitioners in the areas of e.g., precision agriculture and civil defense such as fire fighting. At the same time, as UAVs become a house-hold item, a plethora of issues—which can no longer be ignored and considered niche problems—are coming of age. These range from legal and ethical questions to technical matters such as how to implement and operate a communication infrastructure to maintain control over deployed devices. With these issues being addressed, approaches that focus on enabling collectives of devices to operate semi-autonomously are also increasing in relevance. In this article we present a nature-inspired algorithm that enables a UAV-swarm to operate as a collective which provides real-time data such as video footage. The collective is able to autonomously adapt to changing resolution requirements for specific locations within the area under surveillance. Our distributed approach significantly reduces the requirements on the communication infrastructure and mitigates the computational cost otherwise incurred. In addition, if the UAVs themselves were to be equipped with even rudimentary data-analysis capabilities, the swarm could react in real-time to the data it generates and self-regulate which locations within its operational area it focuses on. The approach was tested in a swarm of 25 UAVs; we present out preliminary performance evaluation.
Highlights
Unmanned Aerial Vehicles (UAVs) [1], often referred to as drones by non-technical users, are known in the academic literature under a variety of names: UASs (Unmanned Aerial Systems) [2], RPAs (Remotely Piloted Aircrafts) [3], ROAs (Remotely Operated Aircrafts) [4] or, mainly, UAVs.While this technology is not new ([5], reports on the U.S military using UAVs for operations as far back as the Vietnam War) it has recently become commercially available to civilian professional users as well as hobbyists
In this article we present a nature-inspired algorithm that enables a UAV-swarm to operate as a collective which provides real-time data such as video footage
The Intelligent Autonomous Systems (IAS) group at TNO is taking steps to partner with the Dutch Military to conduct a series of preliminary tests over military terrain with the express goal to facilitate the testing and operating of UAVs in full autonomy
Summary
Unmanned Aerial Vehicles (UAVs) [1], often referred to as drones by non-technical users, are known in the academic literature under a variety of names: UASs (Unmanned Aerial Systems) [2], RPAs (Remotely Piloted Aircrafts) [3], ROAs (Remotely Operated Aircrafts) [4] or, mainly, UAVs. The use of drones for preliminary data collection is becoming common practice for civilian applications in the areas of, for example, precision agriculture [8] and civil defense such as fire fighting [9], traffic management [10] or to locate victims [11]. For the foreseeable future regulatory bodies will continue to impose different regulations and classifications on UAVs [13]. The available devices differ in manufacturer, type and capabilities and have been used for a wide variety of applications and missions. Special purpose UAVs can remain in the air for up to two weeks [15] or longer and as technologies continue to improve these performance values are only expected to get better [16]
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