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Organisationseinheit der BAM
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
This presentation gives an introduction to the gas-sensitive aerial robots developed at BAM, including various application examples in the field of mobile robot olfaction: gas source localization and gas distribution mapping.
Using a swarm of copter-based gas-sensitive aerial nano robots for monitoring indoor air quality is challenging due to, e.g., limited air space in buildings. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined to guarantee a safe operation of the swarm.
The key contributions of this paper are the realization of experiments that investigate the influence of the rotor downwash on flying vertically displaced nano robots and the development of a model describing the above-mentioned safety region.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.