Soichiro Tsuda

Robot Control with Biological Cells

At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robots actuators.

On-chip electrical impedance tomography for imaging biological cells.

Electrical impedance tomography is an imaging technology that spatially characterizes the electrical properties of an object. We present a miniaturized electrical impedance tomography system that can image the electrical conductivity distribution within a two-dimensional cell culture. A chip containing a circular 16-electrode array was fabricated using printed circuit board developing technology and used to inject current and to measure spatial voltage across the object. The signal stimulation and voltage data acquisition were performed using an impedance analyzer, operating in four-electrode mode. An open source software, EIDORS was used for image reconstruction. Finite element modelling was used to simulate the image reconstruction process by imaging two ellipsoidal phantoms in the circular 16-electrode array. The effect of the regularization parameter in the reconstruction algorithm and the influence from noise on the fidelity of the images has been numerically analyzed. Experimentally, we show reconstructed images of a multi-nuclear single cellular organism, Physarum Polycephalum, demonstrating the first step towards impedance imaging of single cells in culture. Our system provides a non-invasive lab-on-a-chip technology for spatially mapping the electrical properties of single cells, which would be significant and useful for diagnostic and clinical applications.

Robot control: from silicon circuitry to cells

Life-like adaptive behaviour is so far an illusive goal in robot control. A capability to act successfully in a complex, ambiguous, and harsh environment would vastly increase the application domain of robotic devices. Established methods for robot control run up against a complexity barrier, yet living organisms amply demonstrate that this barrier is not a fundamental limitation. To gain an understanding of how the nimble behaviour of organisms can be duplicated in made-for-purpose devices we are exploring the use of biological cells in robot control. This paper describes an experimental setup that interfaces an amoeboid plasmodium of Physarum polycephalum with an omnidirectional hexapod robot to realise an interaction loop between environment and plasticity in control. Through this bio-electronic hybrid architecture the continuous negotiation process between local intracellular reconfiguration on the micro-physical scale and global behaviour of the cell in a macroscale environment can be studied in a device setting.

The emergence of synchronization behavior in Physarum polycephalum and its particle approximation

The regeneration process of contractile oscillation in the plasmodium of Physarum polycephalum is investigated experimentally and modelled computationally. When placed in a well, the Physarum cell restructures the body (fusion of small granule-like cells) and shows various complex oscillation patterns. After it completed the restructuring and regained synchronized oscillation within the body, the cell shows bilateral oscillation or rotating wave pattern. This regeneration process did not depend on the well size and all the cases tested here showed similar time course. Phase synchronization analysis based on Hilbert Transform also suggested that the cell can develop a fully synchronized oscillation within a fixed time no matter what the cell size is. A particle-based computational model was developed in order to model the emergence of oscillation patterns. Particles employing very simple and identical sensory and motor behaviors interacted with each other via the sensing and deposition of chemoattractants in a diffusive environment. From a random and almost homogeneous distribution, emergent domains of oscillatory activity emerged. By increasing the sensory radius the model simulated the regeneration process of the real plasmodium. In addition, the model replicated the rotating wave and bilateral oscillation pattern when the sensory radius was increased. The results suggest that complex emergent oscillatory behaviors (and thus the high-level systems which may utilize them, such as pumping and transport mechanisms) may be developed from simple materials inspired by Physarum slime mold.

Towards Physarum engines

The slime mould Physarum polycephalum is a suitable candidate organism for soft-matter robotics because it exhibits controllable transport, movement and guidance behaviour. Physarum may be considered as a smart computing and actuating material since both its motor and control systems are distributed within its undifferentiated tissue and can survive trauma such as excision, fission and fusion of plasmodia. Thus it may be suitable for exploring the generation and distribution of micro-actuation in individual units or planar arrays. We experimentally show how the plasmodium of Physarum is shaped to execute controllable oscillatory transport behaviour applicable in small hybrid engines. We measure the lifting force of the plasmodium and demonstrate how protoplasmic transport can be influenced by externally applied illumination stimuli. We provide an exemplar vehicle mechanism by coupling the oscillations of the plasmodium to drive the wheels of a Braitenberg vehicle and use light stimuli to effect a steering mechanism. Using a particle model of Physarum we show how emergent travelling wave patterns produced by competing oscillatory domains may be used to to generate spatially represented actuation patterns. We demonstrate different patterns of controllable motion, including linear, reciprocal, rotational and helical, and demonstrate in simulation how dynamic oscillatory patterns may be translated into motive forces for simple transport of substances within a patterned environment.

Single cell imaging using electrical impedance tomography

Electrical impedance spectroscopy is a non-invasive technology for characterizing the dielectric properties of biological tissues and cells. Electrical impedance tomography extends impedance measurements from one dimension to two or three dimensions. Impedance measurements are performed across multiple electrodes, mapping the conductivity distribution within an object. In this paper, electrical impedance tomography is used to image a multi-nucleated cell, Physarum polycephalum, growing on agar gel in a miniaturized chip containing a circular 16-electrode array. An impedance analyzer combined with a USB-controlled multiplexing circuit board is used to perform adjacent impedance measurements. An open source software, EIDORS is used for image reconstruction and the system is evaluated using finite element modeling. Experimentally, a preliminary reconstructed image of Physarum is shown. The system has the potential to monitor kinetics of cells culture.

The Phi-Bot: A Robot Controlled by a Slime Mould

Information processing in natural systems radically differs from current information technology. This difference is particularly apparent in the area of robotics, where both organisms and artificial devices face a similar challenge: the need to act in real time in a complex environment and to do so with computing resources severely limited by their size and power consumption. Biological systems evolved enviable computing capabilities to cope with noisy and harsh environments and to compete with rivalling life forms. Information processing in biological systems, from single-cell organisms to brains, directly utilises the physical and chemical processes of cellular and intracellular dynamics, whereas that in artificial systems is in principle independent of any physical implementation. The formidable gap between artificial and natural systems in terms of information processing capability [1] motivates research into biological modes of information processing. Hybrid artifacts, for example, try to overcome the theoretic and physical limits of information processing in solid-state realisations of digital von Neumann machines by exploiting the self-organisation of naturally evolved systems in engineered environments [2, 3]. This chapter presents a particular unconventional computing system, the Φbot, whose control is based on the behaviour of the true slime mould Physarum polycephalum. The second section gives a short introduction to the informationprocessing capabilities of this organism. The third section describes the two generations of the Φ-bot built so far. To discuss information-theoretic aspects of this robot it is useful to sketch the concept of bounded computability that

Towards Physarum Robots

The true slime mould Physarum polycephalum is a suitable candidate organism for small scale robotics because it spontaneously generates transport, movement and navigation, exhibiting complex behaviour from very simple component interactions. Physarum may be considered as a smart computing material as its motor and control systems are distributed within a simple tissue type and can survive trauma such as excision, fission and fusion of plasmodia. We demonstrate experimentally how the plasmodium of Physarum may be configured to generate complex and controllable oscillatory transport behaviour which may prove useful in small robotic devices. We measure the lifting force of the plasmodium and demonstrate how protoplasmic transport can be influenced by externally applied illumination stimuli. We provide an exemplar vehicle mechanism by coupling the oscillations of the plasmodium to drive the wheels of a Braitenberg vehicle and use light stimuli to effect a steering mechanism. To explore the generation of complex behaviour from such simple component parts we present a particle based model of Physarum which spontaneously generates complex oscillatory patterns from simple local interactions, is distributed in terms of the origin and control of motor behaviour, is morphologically adaptive, is amenable to external influence, and is robust to environmental insult and thus can itself be considered as a virtual smart material. We demonstrate different forms of controllable motion, including linear, reciprocal, rotational, helical, and amoeboid movement.We enable external control of the robotic movement by simulated chemo-attraction (‘pulling’) and simulated light hazards (‘pushing’). The amorphous and distributed properties of the collective are demonstrated by cleaving it into two independent entities and fusing two separate entities to form a single device, thus enabling it to traverse difficult or separate paths. We conclude by examining ways in which future robotic devices may be developed using physical instances of smart materials.

Emergence and Collapse of Order in Ad Hoc Cellular Automata

A system that shows life-like properties requires moderate complexity, so-called the “edge of chaos” state. To investigate how such state is maintained by a system in which agents have limited access to the information about other agents, a simple cellular automata-based model, called ad hoc cellular automata (ACA) is designed and its behaviour is examined. This model shows complex Class 3-like pattern and follows a power law relation. It is also found that the classification of the model is totally different from elementary cellular automata in terms of entropy.