Volume XLII-2/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W6, 5-12, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W6-5-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W6, 5-12, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W6-5-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Aug 2017

23 Aug 2017

DISTRIBUTED UAV-SWARM-BASED REAL-TIME GEOMATIC DATA COLLECTION UNDER DYNAMICALLY CHANGING RESOLUTION REQUIREMENTS

M. Almeida1, H. Hildmann2, and G. Solmaz1 M. Almeida et al.
  • 1NEC Laboratories Europe, Kurfürsten-Anlage 36, 69115 Heidelberg, Germany
  • 2Universidad Carlos III de Madrid (UC3M), Av. Universidad, 30 – 28911 Leganés, Spain

Keywords: Self-organization, adaptive behaviour, swarm algorithms, distributed sensing, autonomous decision making

Abstract. Unmanned Aerial Vehicles (UAVs) have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities – and due to the massive reduction in cost and size – UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency response units. In this paper we present a swarm algorithm that enables a fleet of autonomous UAVs to collectively perform sensing tasks related to environmental and rescue operations and to dynamically adapt to e.g. changing resolution requirements. We discuss the hardware used to build our own drones and the settings under which we validate the proposed approach.