Shinya Kotosaka

Acquisition and contextual switching of multiple internal models for different viscous force fields.

Humans can learn an enormous number of motor behaviors in different environments. To explain this, the MOSAIC model proposes that multiple internal models are acquired in the brain, which can be switched. However, previous behavioral studies that examined arm-movement adaptations to multiple environments reported a rather limited learning capability. Hitherto, humans have been believed incapable of learning two opposite viscous force fields, which are both dynamic transformations and depend on the same state variable, presented in a random order with only a visual cue. In contrast, this study found that humans are capable of this. Elbow joint movements to specified targets were perturbed by either resistive or assistive viscous force fields generated by a single degree-of-freedom manipulandum. The resistive or assistive viscous force fields were cued by a blue or red color on a CRT screen, respectively. The squared distance between the end point and the target, and the variance of the joint angular velocities were used as kinematic performance indices. These movement errors decreased significantly as a function of the training days. Aftereffects and learning consolidation were demonstrated in the random presentation of the two force fields. Consequently, humans were able to learn the multiple and distinct internal models of the two force fields and appropriately switch them even for a random presentation cued only by color after several days of training. This study suggests that none of the previously proposed conditions for multiple internal model learning are necessary prerequisites, and indicates that the difficulty in learning is determined by the balance between the effectiveness of contextual information and the similarity of force fields.

An infra-red sensory system with local communication for cooperative multiple mobile robots

Distributed autonomous robotic systems which are composed of multiple robotic agents have been attracted the attention of many researchers as a new strategy for flexible and robust robotic systems. For cooperative multiple mobile robots in distributed autonomous robotic systems, recognition of the dynamic environment is required. In this paper, a new sensory system with local communication functionality is developed utilizing infra-red devices. Based on the discussion on sensing and communication for cooperative multiple mobile robots, requirements for the sensory system are derived. Then, the infra-red sensory system is designed and developed taking account of the required function. This system enables not only detection of collisions against obstacles or other robots but also local communication between robots. This system can also detect interference of plural infra-red signals. Finally the developed system as introduced, and its performance obtained as a results of experiments is shown.

Collision avoidance among multiple autonomous mobile robots using LOCISS (locally communicable infrared sensory system)

Collision avoidance is an essential problem for applications of multiple mobile robots. The authors have proposed new sensor system called LOCISS (Locally Communicable Infrared Sensory System) to detect robots and obstacles using infrared local communication. Robots mounting LOCISS can exchange useful information for collision avoidance such as speed and moving direction. In this paper, a set of rules for collision avoidance among multiple autonomous mobile robots using LOCISS is proposed. Each robot mutually carries out collision avoidance using the proposed rule. The validity of this set of rules is shown through a series of experiments using mobile robots.

Fault tolerance of a functionally adaptive and robust manipulator

The authors describe the basic design of Fun-ARM, and discuss the strategy of the fault tolerance on distributed manipulator. The fault model is described, and assumptions in the system are discussed. The methods to realize fault tolerance are proposed, including methods for fault-detection, fault-localization and fault-containment.

An Intelligent Data Carrier System for Local Communication Between Cooperative Multiple Mobile Robots and Environment

Abstract This paper presents an intelligent communication device called IDC (Intelligent Data Carrier) designed for local communication within a distributed system with multiple mobile robots. The IDC system is designed as a complement to an existing radio communication system. and is intended to decrease the need for global coordinative communication by providing distributed local inter-robot communication and a local information management function. The IDC system utilizes RF-ID (Radio Frequency Identification) electromagnetic wave transmission for communication, and the units are equipped with a data processing unit and a power unit to allow intelligent autonomous operation. As a result of the autonomy and the portability of the units, the IDC system does not only reduce the load on the global communication system, but it also provides a distribution of intelligent communication devices that enable a variety of interesting robot-environment communication capabilities. In a first example of utilization, the IDC system is used to replace the centralized control in an object transportation system consisting of multiple mobile robots.

Development of ASURA I: Harvestman-like hexapod walking robot — Approach for long-legged robot and leg mechanism design

In this paper, a harvestman-like hexapod walking robot named ASURA I is proposed and its leg mechanism design is discussed. Modeled on a harvestman in nature, the authors have introduced the concept of mobile form that has long legs and small body to ASURA I to enhance mobile performance on rough terrain. To develop long legs relative to body, special parallel link mechanism to drive leg joints powerfully and effectively is introduced to leg mechanism of ASURA I. First, we discuss design problems of leg mechanism in detail: leg length, DOF configuration, actuator selection and leg driving system. Then, analysis of kinematics, singularity and static characteristic of leg mechanism are reported. Finally, the prototype leg, which is 1.3 m in length and 3.2 kg in weight, has been developed and tested on some basic performance. The prototype successfully have demonstrated very basic motion.

Humanoid robot “DB”

Abstract: In this paper, we discuss what kinds of capabilities are needed for a humanoid robot for brain science, introduce our humanoid robot DB, and outline our current research topics concerning this experimental setup.

Reciprocal excitation between biological and robotic research

While biological principles have inspired researchers in computational and engineering research for a long time, there is still rather limited knowledge flow back from computational to biological domains. This paper presents examples of our work where research on anthropomorphic robots lead us to new insights into explaining biological movement phenomena, starting from behavioral studies up to brain imaging studies. Our research over the past years has focused on principles of trajectory formation with nonlinear dynamical systems, on learning internal models for nonlinear control, and on advanced topics like imitation learning. The formal and empirical analyses of the kinematics and dynamics of movements systems and the tasks that they need to perform lead us to suggest principles of motor control that later on we found surprisingly related to human behavior and even brain activity.

The ASURA I harvestman-like hexapod walking robot: compact body and long leg design

Graphical Abstract This paper reports the design of a new hexapod walking robot, ASURA I, inspired by the physical features of a harvestman’s behavior. ASURA I has a special mobile form with one compact body and much longer legs than conventional hexapod walking robots. This form enhances the walking performance of the robot on rocky or uneven terrain. Here, we present the design and analysis of the leg mechanism, body structure design, gait planning, and prototype development. The long legs (relative to the body) are managed by special parallel link mechanisms, which powerfully and effectively drive the leg joints. The leg mechanism is analyzed by its kinematics, singularity, and static characteristics. The leg length and weight of ASURA I is 1.3 m and 27 kg, respectively. The alternating tripod and wave gaits of ASURA I are successfully demonstrated in a series of walking experiments. Video abstract Read the transcript Watch the video on Vimeo