Robust Reconstruction of Sensor Swarms Floating through Enclosed Environments

Abstract

A novel type of application for the exploration of enclosed or otherwise difficult to access environments requires large quantities of miniaturized sensor nodes to perform measurements while they traverse the environment in a "go with the flow" approach. Examples of these are the exploration of underground cavities and the inspection of industrial pipelines or mixing tanks, all of which have in common that the environments are difficult to access and do not allow position determination using e.g. GPS or similar techniques. The sensor nodes need to be scaled down towards the millimetre range in order to physically fit through the narrowest of parts in the environments and should measure distances between each other in order to enable the reconstruction of their positions relative to each other in offline analysis. Reaching those levels of miniaturization and enabling reconstruction functionality requires: 1) novel reconstruction algorithms that can deal with the specific measurement limitations and imperfections of millimetre-sized nodes, and 2) improved understanding of the relation between the highly constraint hardware design space of the sensor nodes and the reconstruction algorithms. To this end, this work provides a novel and highly robust sensor swarm reconstruction algorithm and studies the effect of hardware design trade-offs on its performance. Our findings based on extensive simulations, which push the reconstruction algorithm to its breaking point, provide important guidelines for the future development of millimetre-sized sensor nodes.

Go-With-the-Flow Swarm Sensing in Inaccessible Viscous Media

“…This limits the ultrasound wavelength to around the size of the transducer [20], which in turn is limited by the size of the node itself (millimeters to centimeters). True omnidirectionallity cannot be achieved in practice, these non-ideal circumstances are tested in our earlier work in [13].…”

“…5) Error Model: The off-line reconstruction algorithm is robust to deal with failed ranging transactions between node pairs as shown in [13], as long as sufficient other ranging transactions did succeed. The priority of the ranging protocol is therefore that individual failures of ranging transactions should not have a significant effect on the rest of the swarm.…”

“…In [11]- [13], we developed a reconstruction algorithm for range-only distance measurements and studied the effect on a large set of possible types of noise, including multiple measured distances between the same node pair. The reconstruction algorithm is schematically visualized in Fig.…”

“…V. PERFORMANCE EVALUATION Performance metrics are calculated for both the ranging between and the reconstruction of the nodes as also used in [12] and [13].…”

“…In this paper, we extend and incorporate our robust reconstruction algorithm that was shown to be able to deal with highly corrupted distance measurements. In previous work we tested the limits to how severely the distance measurements could be corrupted before reconstruction fails [11]- [13].…”