Combining Visual, Pedestrian, and Collaborative Navigation Techniques for Team Based Infrastructure Free Indoor Navigation

Abstract

BIOGRAPHIES Aiden Morrison received his PhD degree in 2010 from the University of Calgary. Currently, he works as a research scientist at SINTEF Digital. His main research interests are in the areas of GNSS and multiuser collaborative navigation systems. Laura Ruotsalainen received her PhD in pervasive computing from Tampere University of Technology in 2013, and currently works as an associate professor at the University of Helsinki and as a part-time research professor at the Finnish Geospatial Research Institute. Maija Mäkelä received her MSc in Science and Engineering from the Tampere University of Technology in 2016 and is now pursuing a doctoral degree in the same university. She currently works as a research scientist in the Finnish Geospatial Research Institute, focusing on collaborative navigation methods and algorithms. Jesperi Rantanen received his M.Sc. (Tech.) degree in Geomatics from Aalto University School of Engineering, Finland, in 2015 and he is currently pursuing a doctoral degree at the University of Tampere. He works as a researcher at the Finnish Geospatial Research Institute focusing on developing adaptive navigation systems. Nadezda Sokolova received her PhD degree in 2011 from Norwegian University of Science and Technology (NTNU), where she worked on weak GNSS signal tracking and use of GNSS for precise velocity and acceleration determination. Currently, she works as a research scientist at SINTEF Digital, and adjunct associate professor at the Engineering Cybernetics Department, NTNU focusing on GNSS integrity monitoring and multi-sensor navigation.

Collaborative Indoor Positioning Systems: A Systematic Review

“…Regarding stand-alone positioning in the non-collaborative phase, the most used methods were PDR [ 43 , 63 , 92 , 97 , 98 , 100 , 101 , 102 , 106 , 107 , 110 , 117 , 118 , 120 , 123 , 127 , 128 , 129 , 131 , 141 , 144 , 145 , 146 , 147 ], Ranging [ 42 , 46 , 47 , 81 , 93 , 109 , 111 , 113 , 130 , 132 , 144 , 150 ], RSS-based [ 40 , 41 , 43 , 48 , 77 , 84 , 89 , 103 , 123 , 129 ], k -NN [ 63 , 79 , 108 , 114 , 118 , 119 ,…”

“…As with the non-collaborative part, the most used collaborative methods present advantages and drawbacks. The six most used methods were Particle Filter [ 83 , 89 , 93 , 98 , 102 , 117 , 118 , 120 , 123 , 126 , 129 , 136 , 146 , 147 , 149 , 149 ]; Belief Propagation [ 46 , 47 , 96 , 109 , 130 , 131 , 132 , 135 ]; EKF [ 106 , 107 , 115 , 125 , 140 , 141 , 150 ]; Geometric Algorithm [ 43 , 124 , 127 , 134 , 142 , 143 ]; LS [ 45 , 49 , 133 , 137 , 148 ]; Trilateration [ 40 , 41 , 42 , 94 ]. One of the main advantages of the methods based on Particle Filter is their capability of handling non-Gaussian and non-linear estimations; however, their computational complexity increases (increment of the number of particles) as the position accuracy increases.…”

“…M., F. printing-B P.Filter D I-L E PA [ 148 ] 5G 5G RSSI RSSI Coop. Algorithm LS N/S W/I S PA [ 149 ] Wi-Fi Bluetooth F. printing RSSI F. printing-B P. Filter C I-L E PA 2019 [ 141 ] IMU UWB DR TWR PDR-B. M. EKF D W/I E PA [ 140 ] UWB UWB TWR TWR Coop.…”

Improving Computer Vision-Based Perception for Collaborative Indoor Navigation

“…These conditions frequently arise when some but not all members of a team enter a building, denying GNSS to those inside but often still allowing the higher power RTT and communications signals to pass through the building. In this study, decentralized collaborative navigation [4] was pursued in order to allow the cooperating group of users to dynamically fragment and reform without disruption as communication through building material allowed at any given time. While the benefit of decentralized processing is the implicit tolerance of the ensemble to communication dropouts, a primary drawback is the need to mitigate the impact of the circulation of stale data which in this study was addressed through injection of stabilizing noise to the position state of users operating without an external reference.…”

“…The most promising solution for such a group in rescue operations is collaborative navigation [4]. In collaborative navigation, ranges between group members are measured using radio signals such as Ultra-Wide Band (UWB) round trip timing (RTT) signals.…”