Tomoyuki Yamamoto

Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach

Developing self-organised swarm systems capable of adapting to environmental changes as well as to dynamic situations is a complex challenge. An efficient labour division model, with the ability to regulate the distribution of work among swarm robots, is an important element of this kind of system. This paper extends the popular response threshold model and proposes a new adaptive response threshold model (ARTM). Experiments were carried out in simulation and in real-robot scenarios with the aim of studying the performance of this new adaptive model. Results presented in this paper verify that the extended approach improves on the adaptability of previous systems. For example, by reducing collision duration among robots in foraging missions, our approach helps small swarms of robots to adapt more efficiently to changing environments, thus increasing their self-sustainability (survival rate). Finally, we propose a minimal version of ARTM, which is derived from the conclusions drawn through real-robot and simulation results.

Task Allocation for a robotic swarm based on an Adaptive Response Threshold Model

Biological systems are often composed of many well-organized elements, for instance the flock of birds or social insect communities such as bees or ants. However, developing a swarm robotic system with similar functions, which could be flexible and adapt to environmental changes is undoubtedly complex. In order to achieve such high goal, a good task allocation method, which can regulate and achieve an efficient labor division is crucial. In this paper we propose an optimized version of the simple Response Threshold Model [8] using a discretized version of the Attractor Selection paradigm, in order to dynamically change the threshold parameter (θ). Simulation experiments are carried out in order to study the effects of these optimization measures on the performance of a foraging mission. Simulation experiments verified that the resultant optimized model can improve the adaptation capabilities of previous systems, making a swarm of robots able to adapt more efficiently to dynamical situations.

Foraging optimization in swarm robotic systems based on an adaptive response threshold model

Developing an animal-like highly organized swarm system, which is capable to adapt to environmental changes as well as dynamic situations is undoubtedly complex. A good task allocation method, which can regulate and achieve an efficient labor division among the swarm agents is a crucial element for this kind of systems. In this paper, we propose an extended model of the simple Response Threshold Model using a discretized version of the Attractor Selection paradigm in order to dynamically control the threshold parameter. Simulation experiments are carried out with the purpose of studying the effects of these optimization measures on the performance of a foraging mission. Simulation experiments verified that the resultant optimized model can improve adaptation capabilities of previous systems, making a swarm of robots able to adapt more efficiently to dynamical situations, and therefore increase its survival rate. Graphical Abstract

Design and development of a low power Tactile Multi-Sensor Network for robotic systems

This paper describes the design, implementation and experimental results of a low power Tactile Multi-sensor Network for haptic and robotic applications. A whole-body tactile system will provide the robots with awareness of themselves, and a communication channel to translate dermal messages which could contain emotions. Robots with a sense of touch will have an advantage in alertness and responsiveness for future applications. The proposed Tactile System is composed of individual nodes capable of preprocessing information obtained from multiple sensors, with an embedded microcontroller. Thereby, the tactile information could be delivered to upper layers of supervision for higher cognitive processing. The haptic sensor network is biological inspired by the human tactile system which is able to detect vibration, temperature, contact and pressure. The preliminary experiments of the tactile system demonstrate its reliability, high efficiency in power consumption, wiring simplification, and easy manufacturability. These features will allow the multi-sensor network to be scaled to large number of sensors and nodes in order to cover large surfaces of robotic applications.

A fundamental study of light and flexible wearable robot assisting to recover movement functions

Several exoskeleton robots have been developed for use in rehabilitation. These robots help users to execute transitive motion rehabilitation with power assist. We propose a new robotics system that executes automatic movement training using target motion instruction. The proposed robot is wearable with a flexible body like clothes, and is actuated using a wire-driven mechanism. The robotics system determines the desired posture based on the operators posture. The robot executes a wire-driven force display based on the operators pose and the target pose. We developed a prototype of this wearable robot, and verified the force display using wire-driven mechanism. Moreover, we proposed the multi-joint coordinated motion method, and evaluated the mechanical contribution of the proposed method quantitatively using computer simulations. The simulation results confirm that this robot can instruct the coordinated motion.

Studies of motor synergies in generating optimal goal-directed movements in human-like robotic arm

In studies of human motor control, motor synergy hypothesis has been proposed as a solution of the well-known degree-of-freedom problem. On the other hand, controlling complex robots using optimal control also has the increased difficulty of facing the well-known problem of dimensionality. In this paper, performance of motor synergies in application of generating goal-directed movements using optimal control is examined. Results show that computational expense could be reduced while success rate is maintained, when motor synergies with properties of achieving goal optimally are utilized. The performance of utilizing motor synergies with different properties is also investigated. It is found that the same goals can still be achieved utilizing motor synergies which possess energy efficiency properties, with satisfactory success rate and computation expense.

Subthalamic nucleus detects unnatural android movement

An android, i.e., a realistic humanoid robot with human-like capabilities, may induce an uncanny feeling in human observers. The uncanny feeling about an android has two main causes: its appearance and movement. The uncanny feeling about an android increases when its appearance is almost human-like but its movement is not fully natural or comparable to human movement. Even if an android has human-like flexible joints, its slightly jerky movements cause a human observer to detect subtle unnaturalness in them. However, the neural mechanism underlying the detection of unnatural movements remains unclear. We conducted an fMRI experiment to compare the observation of an android and the observation of a human on which the android is modelled, and we found differences in the activation pattern of the brain regions that are responsible for the production of smooth and natural movement. More specifically, we found that the visual observation of the android, compared with that of the human model, caused greater activation in the subthalamic nucleus (STN). When the android’s slightly jerky movements are visually observed, the STN detects their subtle unnaturalness. This finding suggests that the detection of unnatural movements is attributed to an error signal resulting from a mismatch between a visual input and an internal model for smooth movement.

Automated Courier Transport on the Rail Network: Concept and its Feasibility

A concept for an automated rail-road intermodal courier service system is proposed. While rail transport suffers a number of difficulties, such as long exchange time, large container size and slow speed, the proposed system aims to solve them using ITS-aided transfer robots and an ICT-based routing system. The system is based on a loosely coupled design by which the flexibility of rail networks can be utilized. We investigated the feasibility of the proposed system in economical, physical and technological aspects and obtained positive results. This system copes with aging society, and future industry needs for automation and just-in-time delivery of small packets.

A Concept of Exoskeleton Mechanism for Skill Enhancement

While common implementation of the exoskeleton mechanism is “powered suit” with onboard power plant, it suffers low power-to-weight ratio and often fails to inefficacy problem. On the other hand, quasi-passive mechanism can exploit human efficiency further, which can be regarded as a “wearable bicycle”. In this approach, we are developing an exoskeleton mechanism as a hybrid system for improving users’ skills.