International Journal of Humanoid Robotics

In this paper, an walking pattern tuning system based on (zero moment point) ZMP for a humanoid robot is proposed. Commonly, programming and languages used for developing a humanoid robot are highly sophisticated or complex. The proposed walking pattern tuning system is a program tool to finely tune the walking pattern based on ZMP by adjusting intuitive parameters that common user can understand easily. The walking pattern tuning system was applied to the humanoid robot of 1.1 meters tall and the humanoid robot with the tuned walking pattern was tested for its performance.

In this paper, a motion editing tool to create dancing motions of a humanoid robot is proposed. In order to build performances or dancing of a humanoid robot, a motion editing tool to create specific motions is necessary. Especially, to generate more natural motions is required for a dancing robot. We proposed a motion editing tool and algorithm to create the natural motions. The proposed motion editing tool can create robot's motions composed of several steps which are captured from every joint while the robot plays. The motion editing tool generates the continuous motion interpolated between each steps. A humanoid robot of 50 cm tall is developed to test the proposed tool. The robot using the motion editing tool was demonstrated the natural dancing performance.

The location determination technology (LDT) is one of the core techniques for the location-based services (LBS) which has various applications, including a mobile robot, for the modern wireless communication system. The time of arrival (TOA), which is a kind of LDTs based on the cellular network, estimates the location of the specific user or object using a trilateration method based on the received signals from three base stations (BS). The true location of a mobile station (MS) is determined based on an intersection point of three circles with the radius corresponding to the distance between each BS to MS. Since the TOA method estimates the distance between BS and MS using the number of time delay, these three circles should not generally meet at a point and the performance of the location detection should be degraded in this case. In order to overcome this problem, we propose the mobile location detection algorithm based on a line intersection of the TOA geometry. In the case of those three circles do not meet at a point; in general, there are six intersection points and three lines which connect two intersection points. In this paper, we determine an intersection point of three lines as the location of a MS. The computer simulation example is provided to illustrate the location detection performance of the proposed algorithm.

Smart robots and smart services using robots are promising research fields in academia and industry. However, those smart services are based on basic motions of the robot, such as grabbing objects, and moving them to a designated place. In this paper, we propose a way to produce new motions without programming, from existing motions, through a motion composition method. Our motion composition method utilizes an Action Petri net, which is a variance of a Petri net, with both interpolation and composition operations on a transition. In the Action Petri net, a place is a posture or a moving action of a robot, and it is represented as a diagonal matrix with the robot's joint motor values. Robot motions can be generated from one posture to another posture, and from composing different postures and moving actions. All operations performed to generate new motions are carried out as matrix manipulation operations. Our approach provides a formal method to generate new motions from existing motions, and a practical method to create new motions in low level motion control, without programming.

With the development of computing technology, robots are now popular in our daily life. Human–robot interaction is not restricted to a direct communication between them. The communication could include various different human to human interactions. In this paper, we present a framework for enhancing the interaction among human–robot-environments. The proposed framework is composed of a robot part, a user part, and the DigiLog space. To evaluate the proposed framework, we applied the framework into a real-time remote robot-control platform in the smart DigiLog space. We are implementing real time controlling and monitoring of a robot by using one smart phone as the robot brain and the other smart phone as the remote controller.

Currently, most industrial automation systems and robotic systems require the high-speed transmission of data and highly precise control. We introduce a new communication protocol that is immune to the electromagnetic compatibility (EMC) effect, and is able to reduce the space used in internal robots with limited space. In this paper, we present a novel optical-EtherCAT communication method to reduce EMC, to provide high-speed communication between each module, and to offer real-time control and flexible topology in the internal robot. Then, we verify the communication performance between the proposed optical-EtherCAT communication and previously established EtherCAT communication method. We use the transmission speed, frame size, usage rates of bandwidth, update speed, and cycle time of transmission as evaluation criteria.

This paper is concerned with the stability and the stabilization problem for Takagi–Sugeno (T–S) fuzzy systems with neutral time delays. The sufficient stability conditions are derived using novel Lyapunov–Krasovskii functionals (LKFs). The stability conditions are expressed as linear matrix inequalities (LMIs) and hence easily tractable numerically. These conditions are easily extended to the sufficient conditions for the existence of stabilizing state-feedback fuzzy gains for T–S fuzzy neutral systems with time-varying delays. An example is given to illustrate the effectiveness of the proposed methods.

This paper is concerned with an imitative neural mechanism for recognizing behavior intention in human–robot interaction system. The intention recognition process is inspired by the neural mechanism of the mirror neurons in macaque monkey brain. We try to renovate a standard neural network with parametric biases as a reference model to imitate between sensory-motor data pair. The imitation process is primarily directed toward reproducing the goals of observed actions rather than the exact action trajectories. Several experiments and their results show that the proposed model allows to develop useful robotic application for human–robot interaction system application.

A key technology of the next generation robots is the ability to move with high speed, high precision and communication network control. We propose a vector control system by applying optical-EtherCAT to PMSM with two-axes. We describe configurations of hardware and software to vector control of PMSM with two-axis using an optical-EtherCAT and explain two phase coordinate transformations of the d-q-axis that is the basis of vector control with an optical EtherCAT. We also report results of vector current control, vector current and speed, and vector current and position control of PMSM with two-axes for proposed optical EtherCAT. We confirm that we achieved satisfactory control results due to vector control implemented with an optical EtherCAT.