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 an R and an L for 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-tendency L or turning- tendency R

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

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