iros2019国际学术会议论文集experimental analysis of the influence of olfactory property onchemical plume tracing perance_W

1、IEEE Robotics and Automation Letters (RAL) paper presented at the2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Macau, China, November 4-8, 2019Experimental Analysis of the Influence of Olfactory Property on Chemical Plume Tracing PerformanceShunsuke Shigaki1, Kei Ok

2、ajima2, Kazushi Sanada3 and Daisuke Kurabayashi4stages 45: (1) finding a plume, (2) tracing the chemical plume, and (3) identifying the odor source. In this research, we focus on chemical plume tracing (CPT) of stage (2) which dominantly and intermittently uses olfactory sensing . In the case of sta

3、ge (2), there are many search algorithms based on bio-inspired or statistical methods from previous studies 678910. In the literature 1112, they comprehen- sively examined using simulation and an actual machine and they found that the difference in the search strategy affects CPT performance. Moreov

4、er, it was reported that the mechanism of intaking odorants is closely related to CPT performance 22. However, the influence of odor sensors with different characteristics on the search performance has not been investigated. In particular, there are almost no studies that directly compare the differ

5、ence between living organisms and artifacts with regard to olfactory sensing.Therefore, in this study, we compare the odor sensor of an organism (insect) with artificial odor sensors and investigated whether the difference in characteristics affects CPT performance.II. PROBLEM STATEMENTIn this study

6、, we investigate the difference in the CPT per- formance caused by differences in the response performance of an odor sensor and identify the sensor characteristics that are suitable for olfactory sensing in a robotic system.Although insects have few neurons compared to mammals, they are well adapte

7、d to using olfactory sensing and can readily locate feeding sites and mating partners. However, a robotic system encounters difficulty when using olfactory sensing because odorants have low temporal/spatial resolu- tion and high uncertainty. Therefore, in this investigation, we consider the extent o

8、f the difference between an insect and a machine at the receptor (sensor) level and the effect on the CPT performance. In addition, we performed a CPT experi- ment using moth and an autonomous robot and investigated the relationship between odor sensor characteristics and CPT performance.A male silk

9、worm moth was used (Bombyx mori) as the insect for comparison with the artificial sensors. These insects were used because of a one-to-one relation between the stimulus input (pheromone) and the behavior output 13. The body of the silkworm moth is approximately 30 mm long and 10 mm wide. It has two

10、antennae with a length of approximately 6 mm on its head, and it detects bombykol, which is a pheromone released by female silkworm moths to attract mates 14. After emergence, a moth does not perform any spontaneous behavior, including eating and drinking.Abstract In this study, we investigated the

11、relationship between the performance of chemical plume tracing (CPT) and odor sensing property. Tracking of chemical plumes plays an important role because it facilitates the identification of an odor source. Conventional research has focused on the development of CPT algorithms, whereas the influen

12、ce of the performance odor sensors on CPT performance has not been investigated. Therefore, in this study, we first compared the olfactory characteristics of an insect (silkworm moth, Bombyx mori), which has high CPT performance and the characteristics of an artificial odor sensor. In particular, we

13、 focused on and compared the recovery time of the two types of sensors, which plays an important role in the acquisition of odor information. As a result, it was determined that the recovery time for the insect olfactory sensor was 10 times faster than that of the artificial odor sensor. We also exp

14、erimentally evaluated the effect of this difference in the recovery time on CPT performance. CPT experiments using silkworm moths and a robot revealed that there was a correlation between the CPT performance and sensor recovery time. As such, it was demonstrated that it is necessary to improve not o

15、nly the algorithm but also the sensor recovery time improve the CPT performance.Index Terms Chemical Plume Tracing, Electroantenno- gram, Olfactory Property, Bio-inspired robotics.I. INTRODUCTIONBiological organisms acquire information about their ex- ternal environment using various sensory organs

16、and respond according to this information. Among them, olfactory sens- ing has numerous advantages in terms of sustainability and diffusibility compared to physical quantities transmitted by waves such as light and sound. Therefore, it is extensively used as a tool for exploring and communicating in

17、 numerous areas. However, current robotic systems are not well-adapted to using olfactory sensing because chemical (odor) has high uncertainty due to airflow, temperature, and humidity. However, the use of olfactory sensing in a robotic system has high engineering value because of the potential appl

18、ication to life rescue (e.g., by sensing androstenone1) and dangerous object discovery (e.g., by sensing thionyl chloride2). The odor source localization problem refers to the identifying of an odor source based on the odor information in the air 3. Odor source localization is roughly divided into t

19、hree1Shunsuke Shigaki is with the Department of System Innovation, Osaka University, Japan shigakiarl.sys.es.osaka-u.ac.jp2Kei Okajima is with the Department of Mechanical Engineering, Mate-rials Science, and Ocean Engineering, Yokohama National University, Japanokajima-kei-hxynu.jp3Kazushi Sanada i

20、s with the Division of Systems Research, Yokohama National University, Japan sanada-kazushi-snynu.ac.jp4Daisuke Kurabayashi is with the Department of Systems and Control Engineering, Tokyo Institute of Technology, Japan dkurairs.ctrl.titech.ac.jpCopyright 2019 IEEE1 mmAntennaZig-zagSurgeLoopElectrod

21、e(a) Mating dance for locating the femaleTime course StimulusElectrodeZig-zag(Left/Right turn)Fig. 2.Insertion of electrodes into the antenna.(b) State transitiondiagram10 mmAir compressorGlass pipeSensorFig. 1. Female exploratory behavior of male silkworm moth.Absorbent Activated DW cottoncarbonWhe

22、n a moth detects the female sex pheromone, it performs a ”mating dance” to locate the female by moving about as shown in Fig. 1 22. The mating dance can be divided into three states: surge, zig-zag, and loop 15. By repeating three behaviors in response to the pheromone stimulus, the male silkworm mo

23、th can locate the female 15. For these reasons, we employed bombykol in the experiments with the silkworm moth. We kept the silkworm moths in a 16 h:8 h light:dark photoperiod at 26C and 50%-60% relative humidity using an incubator (MIR-154, Sanyo Electric Co., Ltd., Japan) . Moreover, we used adult

24、 male silkworm moths within 3-5 d after eclosion. Furthermore, all experiments were conducted from 9 am to 5 pm because moths are diurnal insects and the serotonin in their brains is highest during this period 16.III. COMPARISON OF PERFORMANCE BETWEEN OLFACTORY SENSING OF AN INSECT AND AN ARTIFICIAL

25、SENSORA. Experimental setup and designIn this chapter, we investigate the difference in response characteristics between insect olfactory sensing(silkworm moth) and an artificial odor sensor.A silkworm moth detects odors and pheromones via olfactory nerve cells on its antennae. After the electrical

26、signal generated by the olfactory cells of the antennae is transmitted to the brain of the silkworm moth, the odor is identified. An approach that involves the use of an elec- troantennogram (EAG) that was proposed by Schneider et al. in the mid-1950s was used to ascertain whether the insect detecte

27、d an odor. The EAG method involves measurement of voltage change with respect to an odor stimulus by inserting electrodes at both ends of an insect s antenna as shown in Fig. 2 17. The EAG signal was recorded on a PC using an amplifier to enhance the very weak biological signals that were detected.

28、With reference to 18, we used an amplifier with a bandpass filter operating in the range 0.1 - 300 Hz and a 50 Hz band stop filter. The detected electrical signals were amplified by a factor of 250. In this study, the EAGFig. 3. Odor stimulation device for sensor response measurement.response is com

29、pared with the response from an artificial odor sensor.We utilized two alcohol sensors as artificial olfactory sensors: MQ-3(Henan Hanwei Electronics Co.,Ltd., China) and MiCS5524 (SGX Sensortech Ltd., Switzerland). The operating principle of both sensors is the same and chemical detection is achiev

30、ed by measuring the device s resistance. These three types of sensors (EAG, MQ-3, and MiCS5524) were set in the sensor attachment position of the experimental setup shown in Fig. 3. The distance between the discharge port made out of a glass pipe and the sensor was set to 10 mm and an odorous substa

31、nce was deposited on filter paper in the glass pipe. The pheromone (Bombykol, 100 ng)was deposited during EAG measurement and ethanol (10 %, 50 l)was used with the MQ-3 and MiCS 5524 sensors. An odor stimulation device 19was used which consisted of an air compressor (MAS-1, AS ONE, Osaka, Japan), th

32、ree gas washing bottles (absorbent cotton, activated carbon and distilled water), a flow meter (RK1710-AIR, KOFLOC, Kyoto, Japan) and a solenoid valve (VT307, SMC Corporation, Tokyo, Japan). As shown in Fig. 3, the air exhausted from the air compressor passed through absorbent cotton, activated carb

33、on and distilled water, adjusted to a constant flow rate of 1.0 L/min using a flowmeter, and finally exposed to the sensor. In this experiment, we measured the output value of the sensor when exposed to a one-shot odor stimulus (open valve duration: 200 ms), and analyzed the characteristics of the r

34、esponse. The output value ofthe sensor was recorded using a PC at a sampling rate of 1 kHz via an A/D converter (USB-6215, National Instruments, USA). We performed ten repetitions of the experiments for each sensor.DAQArduino UnoLoop(Left/Right turn)Surge(Forward-moving)Wait1odor sensor s rise and r

35、ecovery can be represented by a first- order lag system. The period over which the sensor output value rises immediately after the odor stimulus is applied is defined as the rising phase, and the period until the output returns to the baseline after reaching a peak point is defined as the recovery p

36、hase. The response waveform of the sensor can be formulated separately into the rising and recovering phases as shown in Equ. (1).Model EAG1 mmAntennaElectrodeElectrode0.5tt(a) EAG (1 exp() + , (t t t0s)rrsprR(t) =(1)tt1Model MQ-3 exp() + , (t t)pddpdwhere and represent the gain and offset, respecti

37、vely,andtsandtprepresent the rise start time and the peakpoint time, respectively. We define the rise start time as the time when the differential value of the sensor response is a maximum. r and d represent the time constants of the rise and the recovery phase, respectively. The results obtained by

38、 calculating the coefficients of the model (Equ. (1) based on the method of least squares to fit the sensor experimental values are represented by the black lines in Fig. 4. In addition, Table I shows the results obtained for calculation of the time constants of the rising and the recovery phase of

39、EAG, MQ-3, and MiCS5524.TABLE ICOMPARISON OF THE TIME CONSTANT OF EACH SENSOR.0.50(b) MQ-31Model MiCS55240.5EAGMQ-3MiCS5524r sd s0.008450.02170.20713.10.009551.960051015Time sBased on the results, EAG has the smallest time constant in each of the rise and the recovery phase, and MQ-3 had the largest

40、. Focusing on the time constant of the recovery phase, it was determined that the time constant of EAG and MiCS 5524 is different by a factor of approximately10 times different, and the difference between the time constant of MiCS5524 and MQ-3 is about 10 times. As the recovery time gets slower, the

41、 sensor value tends to saturate; therefore, it is difficult to accurately acquire high-frequency odor information 19, 20. For this reason, it is expected that odor information will be lost if the sensor with a long recovery time is used as the olfactory sensor in the robot. However, the investigator

42、 needs to acquire high-frequency odor information because the odor stimulus frequency is correlated to the distance to the odor source 21. Hence, we investigate the effect of this difference in the recovery time on the CPT performance via an experimental study.IV. EXPERIMENTS FOR CPT PERFORMANCE EVA

43、LUATIONA. Configuration of Autonomous Search RobotIn this section, we describe the configuration of an au- tonomous search robot for mounting the artificial sensor. For the autonomous search robot, we employ a palm-sized mobile robot platform that was used in a previous study as shown in Fig. 5(a) 8

44、. The robot is a differential two-wheel(c) MiCS5524Fig. 4.Sensor response to a one-shot odor stimulus.B. Experimental resultsThe response of each sensor to a one-shot odor stimulus is shown in Fig. 4. Fig. 4 (a)(c) shows the results for the EAG, MQ-3 and MiCS5524, respectively. The red line in Fig.

45、4 represents the mean value of the sensor output, and the grey one represents the standard deviation (n = 10). The vertical and horizontal axes of Fig. 4 represent the normalized value of the sensor output value and the elapsed time, respectively. The release timing of the odor stimulus is represent

46、ed by a triangle ” in Fig. 4. In this study, we investigated the influence of the difference between the rise time and the recovery time of the sensor value on the CPT performance against the odor stimulus to normalize the amplitude of each sensor.To quantitatively evaluate the response of the senso

47、rs, we modeled their response waveform based on a previous study20 and calculated the rise and recovery time. According to 20, the rise and recovery time can be determined by calculating the time constant because the response of theNormalized valueNormalized valueNormalized valueStart160 mmWaitWings

48、Detect odorYesNoAntennaeSurgeIntake system(a) Autonomous search robot5 mm(b) Male silkworm mothDetect odorFig. 5. The autonomous search robot and the male silkworm moth.type robot and has an intake system that can install two odor sensors. The silkworm moth exhibited high localization performance us

49、ing the airflow generated by the flapping of its wings 22. For this reason, we introduced a mechanism for the robot to obtain odor substances by itself by mounting a small fan (NMBMAT 1608KL-04W-B59, CWC Groups, USA) on the intake system. The suction airspeed of this system was 0.37 0.021 m/s, which

50、 is the same value asthe suction airspeed caused by the flapping of the wings of the silkworm moth (5(b) 23. Moreover, the weak point of the artificial odor sensor is that it cannot detect high- frequency odor stimuli because of its long recovery time. It was reported that the time resolution can be

51、 improved by identifying the sensor with an auto-regressive using an exogenous input (ARX) model for this problem 19. Hence, the presence or absence of an odorous substance can be determined by applying the ARX model to both the MQ-3 and MiCS5524. In addition, we implemented the silkworm moth-inspir

52、ed CPT algorithm 8 in the robot. Fig. 6 shows a flowchart of the algorithm. As shown in this figure, the silkworm moth-inspired CPT algorithm transits to the surge state during the detection of an odor stimulus in any behavioral state. The control period of the robot was 50 Hz and the linear and ang

53、ular velocities were 26 mm/s andFig. 6. Flowchart of the silkworm moth-inspired CPT algorithm.y0.5 mxWind speed: 0.68 m/sFanOdor (1.0 L/min)Fig. 7. Outline of CPT experiment field.within 600 s, the search is considered to be successful. Bombykol (1000 ng) and ethanol (99.5 %) wereusedas the odor sou

54、rce and an electric fan (PCF-C15, IRISO- HYAMA INC., Japan) was placed above the source to allow it to diffuse. The wind flow environment was generated by the fan. It is possible to operate the head swing of the fan so that a more turbulent environment can be created. The swing angle of the fan and

55、the swing frequency were /2 rad and 0.1 Hz, respectively. We set the wind speed generated by the electric fan at the odor source to approximately0.68 m/s. As an odor source in the CPT experiment, we employed the odor stimulation device described in Chapter III. Thereby, odor discharge can be precise

56、ly controlled using a computer. The discharge frequency was set in this CPT experiment to 1 Hz (open: 0.2 s, close: 0.8 s) because it was determined that the female silkworm moth discharges pheromones at approximately 1 Hz 24. We conducted20 trials at each of the experimental conditions and we venti

57、lated the experimental room for 10 minutes per trial.1 rad/s, respectively, based on the behavioral data of silkworm moth.B. CPT experiment fieldtheWe evaluated the CPT performance from the viewpoint of the search success rate and search time. Experiments were conducted using a silkworm moth and a robot as a searcher to investigate the relationship between the sensor performance and the CPT performance.Fig. 7 shows a