Should Animals Navigating Over Short Distances Switch to a Magnetic Compass Sense?

Magnetoreception can play a substantial role in long distance navigation by animals. I hypothesize that locomotion guided by a magnetic compass sense could also play a role in short distance navigation. Animals identify mates, prey, or other short distance navigational goals using different sensory modalities (olfaction, vision, audition, etc.) to detect sensory cues associated with those goals. In conditions where these cues become unreliable for navigation (due to flow changes, obstructions, noise interference, etc.), switching to a magnetic compass sense to guide locomotion toward the navigational goals could be beneficial. Using simulations based on known locomotory and flow parameters, I show this strategy has strong theoretical benefits for the nudibranch mollusk Tritonia diomedea navigating toward odor sources in variable flow. A number of other animals may garner similar benefits, particularly slow-moving species in environments with rapidly changing cues relevant for navigation. Faster animals might also benefit from switching to a magnetic compass sense, provided the initial cues used for navigation (acoustic signals, odors, etc.) are intermittent or change rapidly enough that the entire navigation behavior cannot be guided by a continuously detectable cue. Examination of the relative durations of navigational tasks, the persistence of navigational cues, and the stability of both navigators and navigational targets will identify candidates with the appropriate combination of unreliable initial cues and relatively immobile navigational goals for which this hypothetical behavior could be beneficial. Magnetic manipulations can then test whether a switch to a magnetic compass sense occurs. This hypothesis thus provides an alternative when considering the behavioral significance of a magnetic compass sense in animals

Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

Unlike current chemical trace detection technology, dogs actively sniff to acquire an odor sample. Flow visualization experiments with an anatomically-similar 3D printed dog’s nose revealed the external aerodynamics during canine sniffing, where ventral-laterally expired air jets entrain odorant-laden air toward the nose, thereby extending the “aerodynamic reach” for inspiration of otherwise inaccessible odors. Chemical sampling and detection experiments quantified two modes of operation with the artificial nose-active sniffing and continuous inspiration-and demonstrated an increase in odorant detection by a factor of up to 18 for active sniffing. A 16-fold improvement in detection was demonstrated with a commercially-available explosives detector by applying this bio-inspired design principle and making the device “sniff” like a dog. These lessons learned from the dog may benefit the next-generation of vapor samplers for explosives, narcotics, pathogens, or even cancer, and could inform future bio-inspired designs for optimized sampling of odor plumes.United States. Department of Homeland Security. Advanced Research Projects Agency (Interagency Agreement HSHQPM-13-X-00107)United States. Air Force (Contract FA8721-05-C-0002)United States. Air Force (Contract FA8702-15-D-0001

Investigation of the response of high-bandwidth MOX sensors to gas plumes for application on a mobile robot in hazardous environments

A custom sensor module has been developed comprising high-bandwidth metal oxide (MOX), low-cost non-dispersive infra-red (NDIR) and miniature solidly mounted resonator (SMR) acoustic sensors for use on a mobile exploration robot. The module has been tested in a wind tunnel in order to evaluate the performance of three MOX sensors (with coatings of PdPt SnO2, WO3 and NiO) to plumes of 2-propanol (concentration < 2.5 ppm). The formation of the VOC (volatile organic compound) plumes was verified through mapping of sensor responses across a grid of 9 positions in the wind tunnel. Fluctuating sensor responses were observed (±5%), demonstrating variation of VOC concentration within the gas plumes. Higher sensor responses were demonstrated with the n-type SnO2 and WO3 based devices (80% and 40% change relative to baseline, respectively) compared to the p-type NiO device (10%). Short plumes of VOC demonstrated the effect of gas pulse broadening, where longer duration responses (10% greater) were observed at locations further from the VOC source (∼0.4 m distance variation tested). Finally, the module was tested in a real-world environment, where plumes of VOC were observed using the MOX sensors and verified using a commercial Photoionization Detector (PID)

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments

Comparing insect-inspired chemical plume tracking algorithms using a mobile robot

Four chemical plume-tracking algorithms have been compared using a mobile robot. These algorithms are based upon hypotheses proposed to explain the plume-tracking behavior of flying insects. They all use information from a wind sensor and a single chemical sensor to determine how the agent should move to locate the source of the chemical plume. The performance of the robot using each of the algorithms was tested in a wind tunnel under a range of wind speeds (0.55, 0.95, and 1.4 m/s) using a model chemical (ionized air). The robot was capable of tracking the ion plume to its source effectively with each algorithm, having an overall success rate of over 85%. The simplest implemented algorithm, surge anemotaxis, was found to be the fastest. However, the shape of the tracking paths observed indicated that this simple algorithm may not explain the plume-tracking behavior of certain insects as well as the other algorithms tested. Further tests are required to see if the surge anemotaxis algorithm remains the most efficient under more realistic wind conditions.Harvey D.J., Tien-Fu Lu and Keller, M.A

Hazardous Chemical Source Localisation in Indoor Environments Using Plume-tracing Methods

Bio-inspired chemical plume-tracing methods have been applied to mobile robots to detect chemical emissions in the form of plumes and localise the plume sources in various indoor environments. Nevertheless, it has been found from the literature that most of the research has focused on plume tracing in free-stream plumes, such as indoor plumes where the chemical sources are located away from walls. Moreover, most of the experimental and numerical studies regarding the assessment of indoor plume-tracing algorithms have been undertaken in laboratory-scale environments. Since fluid fields and chemical concentration distributions of plumes near walls can be different from those of free-stream plumes, understanding of the performance of existing plume-tracing algorithms in near-wall regions is needed. In addition, the performance of different plume-tracing algorithms in detecting and tracing wall plumes in large-scale indoor environments is still unclear. In this research, a simulation framework combining ANSYS/FLUENT, which is used for simulating fluid fields and chemical concentration distributions of the environment, and MATLAB, with which plume-tracing algorithms are coded, is applied. In general, a plume-tracing algorithm can be divided into three stages: plume sensing, plume tracking and source localisation for analysis and discussion. In the first part of this research, an assessment of the performance of sixteen widely-used plume-tracing algorithms equipped with a concentration-distance obstacle avoidance method, was undertaken in two different scenarios. In one scenario, a single chemical source is located away from the walls in a wind-tunnel-like channel and in the other scenario, the chemical source is located near a wall. It is found that normal casting, surge anemotaxis and constant stepsize together performed the best, when compared with all the other algorithms. Also, the performance of the concentration-distance obstacle avoidance method is unsatisfactory. By applying an along-wall obstacle avoidance method, an algorithm called vallumtaxis, has been proposed and proved to contribute to higher efficiencies for plume tracing especially when searching in wall plumes. The results and discussion of the first part are presented in Chapter 4 of this thesis. In the second part, ten plume-tracing algorithms were tested and compared in four scenarios in a large-scale indoor environment: an underground warehouse. In these four scenarios, the sources are all on walls while their locations are different. The preliminary testing results of five algorithms show that for most failure cases, the robot failed at source localisation stage. Consequently, with different searching strategies at source localisation stage, this research investigated five further algorithms. The results demonstrated that the algorithm with a specially-designed pseudo casting source localisation method is the best approach to localising hazardous plume sources in the underground warehouse given in this research or other similar environments, among all the tested algorithms. The second part of the study is reported in Chapter 5 of this thesis.Thesis (MPhil) -- University of Adelaide, School of Mechanical Engineering, 202

匂い源探索における状態依存的な複数感覚統合に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 神崎 亮平, 東京大学教授 下山 勲, 東京大学教授 竹内 昌治, 東京大学特任講師 安藤 規泰, 総合研究大学院大学講師 木下 充代University of Tokyo(東京大学