Perception in real and artificial insects: a robotic investigation of cricket phonotaxis

The aim of this thesis is to investigate a methodology for studying percep¬ tual systems by building artificial ones. It is proposed that useful results can be obtained from detailed robotic modelling of specific sensorimotor mechanisms in lower animals. By looking at the sensory control of behaviour in simple biological organisms, and in working robots, it is argued that proper appreciation of the physical interaction of the system with the environment and the task is essential for discovering how perceptual mechanisms function. Although links to biology, and concern with perceptual competence, are fields of growing interest in Artificial Intelligence, much of the current research fails to adequately address these issues, as the model systems being built do not represent real sensorimotor problems.By analyzing what is required for a model of a system to contribute to ex¬ plaining that system, a particular approach to modeling perceptual systems is suggested. This involves choosing an appropriate target system to model, building a system that validly represents the target with respect to a particular hypothesis, and properly evaluating the behaviour of the model system to draw conclusions about the target. The viability and potential contribution of this approach is demonstrated in the design, implementation and evaluation of a mobile robot model of a hypothesised mechanism for phonotaxis in the cricket.The result is a robot that successfully locates a specific sound source under a variety of conditions, with a range of behaviour that resembles the cricket in many ways. This provides some support for the hypothesis that the neural mechanism for phonotaxis in crickets does not involve separate processing for recognition and location of the signal, as is generally supposed. It also shows the importance of un¬ derstanding the physical interaction of the system's structure with its environment in devising and implementing perceptual systems. Both these results vindicate the proposed methodology

Machine-Insect Interface: Spatial Navigation of a Mobile Robot by a Drosophila

Machine-insect interfaces have been studied in detail in the past few decades. Animal-machine interfaces have been developed in various ways. In our study, we develop a machine-insect interface wherein an untethered fruit fly (Drosophila melanogaster) is tracked to remotely control a mobile robot. We develop the Active Omni-directional Treadmill (AOT) model, and integrate into the mobile robot to create the interface between the robot and the fruit fly. In this system, a fruit fly is allowed to walk on top of a transparent ball. As the fly tries to walk on the ball, we track the position of the fly using the dark field imaging technique. The displacement of the fly will be balanced out by a counter-displacement of the transparent ball, which is actuated by the omni-directional wheels, to keep the fly at the same position on the ball. Then the mobile robot spatially navigates based on the fly movements. The Robotic Operating System (ROS) is used to interface between the ball tracker and the mobile robot wirelessly. This study will help in investigating the fly’s behavior under different situations such as its response to a physical or virtual stimulus. The future scope of this project will include imaging the brain activity on the Drosophila as it spatially navigates towards a stimulus

Biologically inspired learning system

Learning Systems used on robots require either a-priori knowledge in the form of models, rules of thumb or databases or require that robot to physically execute multitudes of trial solutions. The first requirement limits the robot’s ability to operate in unstructured changing environments, and the second limits the robot’s service life and resources. In this research a generalized approach to learning was developed through a series of algorithms that can be used for construction of behaviors that are able to cope with unstructured environments through adaptation of both internal parameters and system structure as a result of a goal based supervisory mechanism. Four main learning algorithms have been developed, along with a goal directed random exploration routine. These algorithms all use the concept of learning from a recent memory in order to save the robot/agent from having to exhaustively execute all trial solutions. The first algorithm is a reactive online learning algorithm that uses a supervised learning to find the sensor/action combinations that promote realization of a preprogrammed goal. It produces a feed forward neural network controller that is used to control the robot. The second algorithm is similar to first in that it uses a supervised learning strategy, but it produces a neural network that considers past values, thus providing a non-reactive solution. The third algorithm is a departure from the first two in that uses a non-supervised learning technique to learn the best actions for each situation the robot encounters. The last algorithm builds a graph of the situations encountered by agent/robot in order to learn to associate the best actions with sensor inputs. It uses an unsupervised learning approach based on shortest paths to a goal situation in the graph in order to generate a non-reactive feed forward neural network. Test results were good, the first and third algorithms were tested in a formation maneuvering task in both simulation and onboard mobile robots, while the second and fourth were tested simulation

Development of PVDF tactile dynamic sensing in a behaviour-based assembly robot

The research presented in this thesis focuses on the development of tactile event sig¬ nature sensors and their application, especially in reactive behaviour-based robotic assembly systems.In pursuit of practical and economic sensors for detecting part contact, the application ofPVDF (polyvinylidene fluoride) film, a mechanical vibration sensitive piezo material, is investigated. A Clunk Sensor is developed which remotely detects impact vibrations, and a Push Sensor is developed which senses small changes in the deformation of a compliant finger surface. The Push Sensor is further developed to provide some force direction and force pattern sensing capability.By being able to detect changes of state in an assembly, such as a change of contact force, an assembly robot can be well informed of current conditions. The complex structure of assembly tasks provides a rich context within which to interpret changes of state, so simple binary sensors can conveniently supply a lot more information than in the domain of mobile robots. Guarded motions, for example, which require sensing a change of state, have long been recognised as very useful in part mating tasks. Guarded motions are particularly well suited to be components of assembly behavioural modules.In behaviour-based robotic assembly systems, the high level planner is endowed with as little complexity as possible while the low level planning execution agent deals with actual sensing and action. Highly reactive execution agents can provide advantages by encapsulating low level sensing and action, hiding the details of sensori-motor complexity from the higher levels.Because behaviour-based assembly systems emphasise the utility of this kind of quali¬ tative state-change sensor (as opposed to sensors which measure physical quantities), the robustness and utility of the Push Sensor was tested in an experimental behaviourbased system. An experimental task of pushing a ring along a convoluted stiff wire is chosen, in which the tactile sensors developed here are aided by vision. Three differ¬ ent methods of combining these different sensors within the general behaviour-based paradigm are implemented and compared. This exercise confirms the robustness and utility of the PVDF-based tactile sensors. We argue that the comparison suggests that for behaviour-based assembly systems using multiple concurrent sensor systems, bottom-level motor control in terms of force or velocity would be more appropriate than positional control. Behaviour-based systems have traditionally tried to avoid symbolic knowledge. Considering this in the light of the above work, it was found useful to develop a taxonomy of type of knowledge and refine the prohibition

Predictive processing and anti-representationalism

Many philosophers claim that the neurocomputational framework of predictive processing entails a globally inferentialist and representationalist view of cognition. Here, I contend that this is not correct. I argue that, given the theoretical commitments these philosophers endorse, no structure within predictive processing systems can be rightfully identified as a representational vehicle. To do so, I first examine some of the theoretical commitments these philosophers share, and show that these commitments provide a set of necessary conditions the satisfaction of which allows us to identify representational vehicles. Having done so, I introduce a predictive processing system capable of active inference, in the form of a simple robotic “brain”. I examine it thoroughly, and show that, given the necessary conditions highlighted above, none of its components qualifies as a representational vehicle. I then consider and allay some worries my claim could raise. I consider whether the anti-representationalist verdict thus obtained could be generalized, and provide some reasons favoring a positive answer. I further consider whether my arguments here could be blocked by allowing the same representational vehicle to possess multiple contents, and whether my arguments entail some extreme form of revisionism, answering in the negative in both cases. A quick conclusion follows

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

MECHANOSENSORY FEEDBACK FOR FLIGHT CONTROL AND PREY CAPTURE IN THE ECHOLOCATING BAT

Throughout the animal kingdom, organisms have evolved neural systems that process biologically relevant stimuli to guide a wide range of species-specific behaviors. Bats, comprising 25% of mammalian species, rely on diverse sensory modalities to carry out tasks such as foraging, obstacle avoidance and social communication. While it is well known that many bat species use echolocation to find food and steer around obstacles, they also depend on other senses. For instance, some bats predominantly use vision to navigate, and others use olfaction to find food sources. In addition, bats rely on airflow sensors to stabilize their flight, primarily through signals carried by microscopic hairs embedded in their wings and tail membranes. Studies have shown that bats performing an obstacle avoidance task show changes in their flight behavior when dorsal wing hairs are removed. Additionally, electrophysiological studies have shown that wing hairs are involved in airflow sensing, but little is known about the contribution of sensory hairs on the ventral surfaces of the wing and tail membranes to their flight control and other complex behaviors, such as prey handling. Chapter 1 of my dissertation presents a general introduction to bat echolocation, flight kinematics, and airflow sensing for flight control. In Chapter 2, I review sensory hairs across the animal kingdom, from invertebrates to vertebrates. I discuss the role of sensory hairs for functions ranging from detection to locomotion and propose the use and benefit of mechanosensors in biologically-inspired technology. In Chapter 3, I devised an experiment to evaluate changes in capture success, as well changes in flight kinematics and adaptive sonar behavior, before and after depilation of sensory hairs in order to ascertain if these sensory hairs have a functional role in both airflow sensing for flight control and tactile sensing for prey handling. In Chapter 4, I designed an experiment aimed at determining if firing patterns of S1 neurons change with airflow speed and angle of attack and if wing hair depilation affects S1 responses to whole wing stimulation. To answer these questions, I record neural activity in S1 of sedated big brown bats while the entire contralateral wing is systematically exposed to naturalistic airflow in a wind tunnel. Finally, in Chapter 5, I address open questions that remain, present experiments aimed at filling these gaps, and consider key points important for future work

Studies Of Sound Propagation In The Acoustic Trachea: An Experimental, Anatomical And Numerical Approach

Bush-crickets (Ensifera: Tettigoniidae) rely on the perception of sound to detect and localise predators and potential mates, and this has led to the development of complex ears. This is not confined to bush-crickets, and a variety of sound detection and localisation mechanisms have arisen in other ensiferans and tetrapods. This thesis aims to summarise the literature across these two groups to provide an overview of auditory anatomy and directional hearing. Bush-crickets possess ears in their forelegs to detect and localise sound predators and potential mates. Each ear consists of two tympanic membranes which are exposed to sound both externally, where sound transmits to the ear through the environment, and internally, via an ear canal derived from the respiratory system. As sound propagates through the ear canal it reduces in velocity, causing a time delay between the arrival of the internal and external input. The delay was suspected to arise as sound propagation changes from adiabatic to isothermal, caused by the ear canal geometry. If true, then the reduction in sound velocity should persist independently of the gas composition in the ear canal. This method was first simulated on a simplified plastic model of the ear canal, formed by a linear tube with an opening at one end for sound input, and a balloon membrane at the other for sound reception. A probe-loudspeaker was used to project a signal into the linear tube, and laser Doppler vibrometer recorded the arrival time of the signal at the membrane. A reduction in sound propagation velocity was observed in the linear tube. The sound propagation velocity through air and carbon dioxide was also quantified. Experiments were then conducted on specimens of Copiphora gorgonensis. By integrating laser Doppler vibrometry, micro-CT scanning, and numerical analysis on 3D geometries of each experimental animal ear, we demonstrate that the narrowing radius of the ear canal is the main factor reducing sound velocity. The numerical simulations of the sound propagation use the precise 3D geometry of the ear canal and take into account the viscous and thermal boundary layers formed near the wall of the ear canal; whose thickness also depend on the tube radius. Likewise, the ear canal is asymmetrically bifurcated at the tympana organ location (one branch for each tympanic membrane) creating two additional internal sound paths and imposing different sound velocities for each tympanic membrane. Therefore, external and internal inputs add up to four auditory paths for each ear (to compare, only one for humans). Implication of findings in avian directional hearing and potential applications in acoustic triangulation devices are discussed

Digital Interaction and Machine Intelligence

This book is open access, which means that you have free and unlimited access. This book presents the Proceedings of the 9th Machine Intelligence and Digital Interaction Conference. Significant progress in the development of artificial intelligence (AI) and its wider use in many interactive products are quickly transforming further areas of our life, which results in the emergence of various new social phenomena. Many countries have been making efforts to understand these phenomena and find answers on how to put the development of artificial intelligence on the right track to support the common good of people and societies. These attempts require interdisciplinary actions, covering not only science disciplines involved in the development of artificial intelligence and human-computer interaction but also close cooperation between researchers and practitioners. For this reason, the main goal of the MIDI conference held on 9-10.12.2021 as a virtual event is to integrate two, until recently, independent fields of research in computer science: broadly understood artificial intelligence and human-technology interaction

Embodied Cognitive Science of Music. Modeling Experience and Behavior in Musical Contexts

Recently, the role of corporeal interaction has gained wide recognition within cognitive musicology. This thesis reviews evidence from different directions in music research supporting the importance of body-based processes for the understanding of music-related experience and behaviour. Stressing the synthetic focus of cognitive science, cognitive science of music is discussed as a modeling approach that takes these processes into account and may theoretically be embedded within the theory of dynamic systems. In particular, arguments are presented for the use of robotic devices as tools for the investigation of processes underlying human music-related capabilities (musical robotics)