Mitsuhiro Yamano

A CORBA‐based approach for humanoid robot control

Recently, many control architectures for robots have been proposed. However, in these architectures, it is difficult to add new functions to existing applications or add new applications. Moreover, developing a robot control system using many researchers makes it difficult to cooperate with each other. In order to deal with these problems, we propose a Humanoid Robot Control Architecture (HRCA) based on Common Object Request Broker Architecture (CORBA). The proposed HRCA is organized as a client/server control architecture. The HRCA is implemented as an integration of many humanoid robot control modules, which correspond to CORBA servers and clients. By applying these to “Bonten‐Maru I” a humanoid robot, which is under development in our laboratory, we describe the HRCA modules and the effectiveness of HRCA. We confirmed the effectiveness of HRCA from simulation and experimental results. By using the proposed HRCA, the control of the humanoid robot in a distributed environment such as a Local Area Network (LAN) is possible and thus various humanoid robots in the world can share their own modules with each other via the Internet.

Low force control scheme for object hardness distinction in robot manipulation based on tactile sensing

This paper presents an application of a low force interaction method in a control scheme of robot manipulation based on tactile sensing. Our aim is to develop an intelligent control system that can distinguish the hardness of unknown objects so that robotic fingers can effectively explore the objects surface without altering its physical properties or causing damage. Initially we developed a novel optical three-axis tactile sensor system based on an optical waveguide transduction method capable of acquiring normal and shearing forces. The sensors are mounted on the fingertips of the multi-fingered humanoid robot arm. We proposed a new control scheme applying low force interaction to distinguish the hardness of unknown objects in robot manipulation tasks based on tactile sensing. The scheme utilized new control parameters obtained by calibration experiments using hard and soft objects that enable robot fingers to precisely control grasp pressure and define the slippage sensation of the given object. Finally, verification experiments of the proposed control scheme using a humanoid robot arm were conducted whose results revealed that the fingers system managed to recognize the hardness of unknown objects and complied with sudden changes of the objects weight during object manipulation tasks.

An Approach Toward an Automated Object Retrieval Operation with a Two-Arm Flexible Manipulator

The recent developments in space technology demand various services to uncontrollable satellites, such as refueling and repairing, in order to extend their lifespans. However, there has so far been no research on such practical applications with flexible manipulators. In this paper, we address automated object capture with a two-arm flexible manipulator, which is a basic technology for such services in space. This object capturing strategy includes symmetric cooperative control, visual servoing, the resolution of the inverse kinematics problem and the optimization of the configuration of a two-arm redundant flexible manipulator. For the performance improvement on the rise time of the internal forces at the instant of making contact, a transition control strategy is also proposed considering the resultant mechanical compliance associated with the internal forces. Moreover, we present the control system configuration for this task. This control system is based on IBM-compatible personal computers (PCs), and the computational loads for the task execution are distributed to several PCs connected to each other through the Ethernet. The effectiveness of the proposed control system and task sequence is validated with the experiments.

Obstacle Avoidance in Groping Locomotion of a Humanoid Robot

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robots control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robots leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a walls surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.

Development of an Optical Three-Axis Tactile Sensor for Object Handing Tasks in Humanoid Robot Navigation System

Summary. Autonomous navigation in walking robots requires that three main tasks be solved: self-localization, obstacle avoidance, and object handling. This report presents a development and application of an optical three-axis tactile sensor mounted on a robotic finger to perform object handling in a humanoid robot navigation system. Previously in this research, we proposed a basic humanoid robot navigation system called the groping locomotion method for a 21-dof humanoid robot, which is capable of defining self-localisation and obstacle avoidance. Recently, with the aim to determining physical properties and events through contact during object handling, we have been developing a novel optical three-axis tactile sensor capable of acquiring normal and shearing force. The tactile sensor system is combined with 3-dof robot finger system where the tactile sensor in mounted on the fingertip. Experiments were conducted using soft, hard, and spherical objects to evaluate the sensors performance. Experimental results reveal that the proposed optical three-axis tactile sensor system is capable of recognizing contact events and has the potential for application to humanoid robot hands for object handling purposes.

Capturing a spinning object by two flexible manipulators

This paper discusses a way of capturing a spinning object using two flexible manipulators. We propose a capturing procedure using hybrid position/force control and vibration suppression control. The procedure is established so that the manipulators capture the object automatically measuring position and rotational velocity of the object. The motion of the two hands of the manipulators are synchronized with the rotation of the object. The hands make contact with the spinning object safely, considering link flexibility, and then brake the spin smoothly. The effectiveness of our method is shown in experiments using two 3D manipulators, each of which has two flexible links and seven joints.

Navigation Strategy by Contact Sensing Interaction for a Biped Humanoid Robot

This report presents a basic contact interaction-based navigation strategy for a biped humanoid robot to support current visual-based navigation. The robots arms were equipped with force sensors to detect physical contact with objects. We proposed a motion algorithm consisting of searching tasks, self-localization tasks, correction of locomotion direction tasks and obstacle avoidance tasks. Priority was given to right-side direction to navigate the robot locomotion. Analysis of trajectory generation, biped gait pattern, and biped walking characteristics was performed to define an efficient navigation strategy in a biped walking humanoid robot. The proposed algorithm is evaluated in an experiment with a 21-dofs humanoid robot operating in a room with walls and obstacles. The experimental results reveal good robot performance when recognizing objects by touching, grasping, and continuously generating suitable trajectories to correct direction and avoid collisions.

A CORBA-Based Control Architecture for Real-Time Teleoperation Tasks in a Developmental Humanoid Robot

This paper presents the development of new Humanoid Robot Control Architecture (HRCA) platform based on Common Object Request Broker Architecture (CORBA) in a developmental biped humanoid robot for real-time teleoperation tasks. The objective is to make the control platform open for collaborative teleoperation research in humanoid robotics via the internet. Meanwhile, to generate optimal trajectory generation in bipedal walk, we proposed a real time generation of optimal gait by using Genetic Algorithms (GA) to minimize the energy for humanoid robot gait. In addition, we proposed simplification of kinematical solutions to generate controlled trajectories of humanoid robot legs in teleoperation tasks. The proposed control systems and strategies was evaluated in teleoperation experiments between Australia and Japan using humanoid robot Bonten-Maru. Additionally, we have developed a user-friendly Virtual Reality (VR) user interface that is composed of ultrasonic 3D mouse system and a Head Mounted Display (HMD) for working coexistence of human and humanoid robot in teleoperation tasks. The teleoperation experiments show good performance of the proposed system and control, and also verified the good performance for working coexistence of human and humanoid robot.

Development of a contact interaction-based navigation strategy for a biped humanoid robot

This paper presents the development of a contact interaction-based navigation strategy for a biped humanoid robot with the aim of supporting current visual-based navigation. The robot arms are equipped with force sensors to detect physical contact with objects. We proposed a motion algorithm consisting of searching tasks, self-localization, correction of locomotion direction and obstacle avoidance. Priority is given to right-side direction to navigate the robot locomotion in conjunction with a strategy to avoid obstacles. The proposed algorithm is evaluated in an experiment with a humanoid robot operating in a room with walls and obstacles. The experimental results reveal good performance of the robot when recognizing objects by touching and grasping, continuously generating suitable trajectory to correct locomotion direction and avoiding collisions.

Real time generation of humanoid robot optimal gait for going upstairs using intelligent algorithms

Going upstairs is a common humanoid robot task. In this paper, a genetic algorithm (GA) gait synthesis method for going upstairs and a radial basis function neural network (RBFNN) implementation, are considered. The gait synthesis is analyzed based on the minimum consumed energy and minimum torque change. The proposed method can easily be applied to generate the angle trajectories for going downstairs, overcoming obstacles, etc. In our work, the stability is verified through the ZMP concept. For the real time implementation, a RBFNN which is taught based on the GA results, is considered. The RBFNN generates the optimal gait in a very short time, where the input variables are the step length, step height and step time. Simulations are realized based on the parameters of the “Bonten‐Maru I” humanoid robot.