TY - CONF A1 - Neumann, Patrick P. A1 - Häusler, F. S. A1 - Stührenberg, J. A1 - Smarsly, K. T1 - Seminar on Smelling Drones – Part 3: Deep Dive: Bout-based Gas Source Localization using Aerial Robot Swarms N2 - This seminar series comprises three lectures on drones and ground robots capable of sensing chemical substances and two accompanying hands-on workshops on nano drones equipped with chemical sensors. In the first lecture, Dr. Neumann will talk on a summary of aerial robot olfaction and his research. In the second and third lectures, more details of the nano drones equipped with chemical sensors will be provided, and the participants can get hands on experience of the nano drones in the accompanying workshops. The lectures will be given in English. This seminar series is supported by FY2023 Researcher Exchanges Program in UEC. T2 - Seminar Series on Smelling Drones CY - Tokyo, Japan DA - 28.11.2023 KW - Mobile robotic olfaction KW - Nano aerial robot KW - Gas source localization KW - Bouts KW - Distributed robotics KW - Swarm PY - 2023 AN - OPUS4-59131 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Häusler, F. A1 - Stührenberg, J. A1 - Smarsly, K. T1 - Bout-based Gas Source Localization using Aerial Robot Swarms N2 - Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration. T2 - IEEE Sensors 2023 CY - Vienna, Austria DA - 29.10.2023 KW - Mobile robotic olfaction KW - Nano aerial robot KW - Gas source localization KW - Bouts KW - Distributed robotics PY - 2023 AN - OPUS4-58779 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Häusler, F. A1 - Stührenberg, J. A1 - Smarsly, K. A1 - Neumann, Patrick P. T1 - Bout-based Gas Source Localization using Aerial Robot Swarms N2 - Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration. T2 - IEEE Sensors 2023 CY - Vienna, Austria DA - 29.10.2023 KW - Mobile robotic olfaction KW - Nano aerial robot KW - Gas source localization KW - Bouts KW - Distributed robotics PY - 2023 SN - 979-8-3503-0387-2 U6 - https://doi.org/10.1109/sensors56945.2023.10325109 SP - 1 EP - 4 PB - IEEE AN - OPUS4-58778 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -