TY - JOUR
T1 - Autonomous gas-sensitive microdrone
T2 - Wind vector estimation and gas distribution mapping
AU - Neumann, Patrick P.
AU - Asadi, Sahar
AU - Lilienthal, Achim J.
AU - Bartholmai, Matthias
AU - Schiller, Jochen H.
N1 - Funding Information:
The authors thank the participating colleagues from BAM and Orebro€ University. They also express their gratitude to BMWi [measurements, standards, testing, and quality assurance (MNPQ) Program; file number 28/07] and to the European Commission [contract number FP7 224318—Distributed Information Acquisition and Decision-Making for Environmental Management (DIADEM)] for funding the research.
Funding Information:
The Federal Institute for Materials Research and Testing [Bundesanstalt fu€r Materialforschung und -pru€fung (BAM)], in cooperation with Airrobot GmbH, has developed a mobile and flexible aerial-based measurement system as part of an R&D project funded by the Federal Ministry of Economics and Technology [Bundesministerium fu€r Wirt-schaft und Technologie (BMWi)] [21]. One result of the project is a gas-sensitive sensor module (approximately 200 g) for the Airrobot AR100-B microdrone (Figure 1).
PY - 2012/3
Y1 - 2012/3
N2 - This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization.
AB - This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization.
UR - http://www.scopus.com/inward/record.url?scp=84859714487&partnerID=8YFLogxK
U2 - 10.1109/MRA.2012.2184671
DO - 10.1109/MRA.2012.2184671
M3 - Article
AN - SCOPUS:84859714487
SN - 1070-9932
VL - 19
SP - 50
EP - 61
JO - IEEE Robotics and Automation Magazine
JF - IEEE Robotics and Automation Magazine
IS - 1
M1 - 6155597
ER -