Autonomous microhelicopters will soon play a major role in tasks like search and rescue, environment monitoring, security surveillance, and inspection. If they are further realized in small scale, they can also be used in narrow outdoor and indoor environments and represent only a limited risk for people. However, for such operations, navigating based only on global positioning system ({GPS}) information is not sufficient. Fully autonomous operation in cities or other dense environments requires microhelicopters to fly at low altitudes, where {GPS} signals are often shadowed, or indoors and to actively explore unknown environments while avoiding collisions and creating maps. This involves a number of challenges on all levels of helicopter design, perception, actuation, control, and navigation, which still have to be solved. The Swarm of Micro Flying Robots ({SFLY}) project was a European Union-funded project with the goal of creating a swarm of vision-controlled microaerial vehicles ({MAVs}) capable of autonomous navigation, three-dimensional (3-D) mapping, and optimal surveillance coverage in {GPS}-denied environments. The {SFLY} {MAVs} do not rely on remote control, radio beacons, or motion-capture systems but can fly all by themselves using only a single onboard camera and an inertial measurement unit ({IMU}). This article describes the technical challenges that have been faced and the results achieved from hardware design and embedded programming to vision-based navigation and mapping, with an overview of how all the modules work and how they have been integrated into the final system. Code, data sets, and videos are publicly available to the robotics community. Experimental results demonstrating three {MAVs} navigating autonomously in an unknown {GPS}-denied environment and performing 3-D mapping and optimal surveillance coverage are presented.     «

Autonomous microhelicopters will soon play a major role in tasks like search and rescue, environment monitoring, security surveillance, and inspection. If they are further realized in small scale, they can also be used in narrow outdoor and indoor environments and represent only a limited risk for people. However, for such operations, navigating based only on global positioning system ({GPS}) information is not sufficient. Fully autonomous operation in cities or other dense environments requires...     »

aerospace computing, aerospace robotics, Aircraft navigation, autonomous mapping, autonomous microhelicopters, autonomous navigation, Batteries, camera, control engineering computing, embedded programming, European Union, Global Positioning System, Global Positioning Systems, {GPS}-denied environment, {GPS} information, hardware design, helicopter actuation, helicopter control, helicopter design, helicopter navigation, helicopter perception, Helicopters, {IMU}, inertial measurement unit, Intelligent vehicles, {MAV}, microrobots, Mobile robots, multi-robot systems, path planning, Payloads, Robot navigation, robot vision, {SFLY} project, Surveillance, swarm of micro flying robots, vision-controlled micro flying robots, peer_review     «

aerospace computing, aerospace robotics, Aircraft navigation, autonomous mapping, autonomous microhelicopters, autonomous navigation, Batteries, camera, control engineering computing, embedded programming, European Union, Global Positioning System, Global Positioning Systems, {GPS}-denied environment, {GPS} information, hardware design, helicopter actuation, helicopter control, helicopter design, helicopter navigation, helicopter perception, Helicopters, {IMU}, inertial measurement unit, Intelli...     »