Using robots to model animals: a cricket test

Barbara Webb

Presenter: Gholamreza Haffari

Bio-Robotics A methodology established to bridge

the gap between Artificial Intelligence & Biology (Kortmann 1998)

Based on the method of “explanation by modeling”

Related fields Neuroethology

Subfield of Biology How animal behavior is rooted in the neural

systems in the animal brain

Computational Neuroethology Studying neural mechanisms that underlie

adaptive behavior by building autonomous agents

Not restricted to modeling existing animals (natural as well as artificial agents)

Related fields (cont.) Animat

Studying natural adaptive systems by building artificial autonomous agents

Belongs to behavior-based approach to AI

Bio-Robotics Methodology Models are built, based on the

hypotheses on neural mechanisms that underlie adaptive behavior in real animals

By careful experimentation with the model and reliable interpretation of its behavior, one can obtain evidence on the hypothesized mechanism modeled

Framework of Modeling

A general framework of modeling (Kortmann 1998)

Modeling animals

It is necessary to accurately represent the real physical interaction of the animal and the environment

Physical environment and physical interactions are extremely complex to model symbolically

Keeping in mind that biological systems are Situated in the environment and interact with it Embodied, i.e. they always have a body

Robots are well suited to being used as physical models of animals

Studying simple animals It is relatively easy to find isolated

adaptive behaviors that are likely to be pre-programmed by a simple direct pathway in their brain

These pathways are expected to be found relatively easily

Phonotaxis behavior of cricket

Ability of the female cricket to find a conspecific male by walking or flying towards the calling song the male produces Conspecific means (individual) from the same

species Getting to the target by constantly adjusting

the direction according to current sensory cues

Directionality and Recognition

How does the cricket identify the correct signal?

How does it detect the difference between two sides, and hence choose which way to turn?

Until now, precise sensory motor control of the phonotaxis behavior has not been found

Webb (1993) decided to design a robot model to give evidence for a hypothesized control mechanism

Mechanisms underlying phonotaxis

The phonotaxis mechanism can be divided into

two components:

The peripheral auditory system (the ears) Its working can be described in the physical level

The brain mechanism Which is described in the language of

neurophysiology

Phonotaxis mechanisms (cont.)

Peripheral auditory system

Consists of:

Two auditory organs located in the forelegs

An H-shaped tracheal tube that leads through the body and have four ends: Two in the forelegs (the tympani) Two at the side of the thorax (the spiracles)

Peripheral auditory organ

(Kortmann 1998)

Physics of the auditory system

In a simplified version, consider only the connection between the two tympani

Two external and internal sound waves reach the tympanum The external signal comes directly from the

source The internal signal comes indirectly from

contralateral tympanum via tracheal tube

Physics of auditory sys. (Cont)

Assume the length between the two tympani to be ¼ of the wavelength of the calling song

Sound waves arrive to the closest tympanum in antiphase from opposite sides, and cause the optimal response of the membrane

But, sound waves arrive in phase to the other tympanum and cause the minimal response

Phase cancellation

Robot’s auditory mechanism

Two miniature microphones positioned 4.5 cm apart from each other (1/4 the wavelength of the 2 kHz signal used)

Input at the left ear is combined with the delayed signal from the right ear:

The same occurs for the right ear

Comparing the response Signals of auditory receptors are carried

by auditory nerves to small number of interneurons, one pair of these (AN1) appears particulary receptive

The comparison can be based on the Firing rate Latency

Robot’s comparison mechanism

Response-dependent latency is implemented in the robot by using summation with decay

Consider variables anR and anLfor each ear, where for each variable:

Each an fires when it is >= 8 (behaves like a low-pass filter)

The comparison then occurs in the module COMPARE (based on the onset of an variables), increasing the value of turning-tendencyLor turning-tendencyR

Terminology in describing songs

(Kortmann 1998)

Experiments setup

Frequency: 2 kHz Syllable repetition

rate: 1.6 Hz

Speaker and Robots starts positions

Locating the sound source

Locating the sound source with obstacles

Recognizing the sound source Is the behavior selective, i.e. does the robot

approach no-ideal sound sources?

Slow syllable rate (1 Hz) Fast Syllable rate (2.5 Hz)

Effect of chirps The syllables are repeated only a few

times and these groups (chirps) are separated by equal length of silence

Without chirps, there is a certain amount of vacillation in the approach to the sound

By chirps, cricket makes only occasional adjustment of heading rather than continual adjustment

Effect of chirps (cont.)

Three-syllable chirps at the rate of 3 Hz

Choice phenomenon Female cricket seems able to “choose”

to approach directly just one singing male despite a number of other males also singing well within auditory range

Does it imply “central complex processing” ?

No, it can be seen in the behavior our simple robot

Choice phenomenon (cont.)

Discussion Understanding biological systems provide a

set of “tricks” that may usefully be adapted for robotics

Furthermore, they lead to better explanation of the behavior

The mechanisms in biological systems are the result of the “evolution” and thus may rarely represent ideal methods for achieving the task but they are “good enough”

Using simulation model?

“Even in the most exhaustive simulations some potentially important effects may be neglected, overlooked or improperly modeled”

“It is often not reasonable to attempt to account for the complexity and unpredictability of the real world”

Conclusion

The links between biology and robotics have tended to be at an abstract level At the level of behavior Not representing sensory transduction,

neural processing and motor control Detailed attention to one highly specific

animal competence will contribute to a general understanding of the functioning of sensorimotor mechanisms

Thanks