Kimitoshi Yamazaki

Home-Assistant Robot for an Aging Society

Many countries around the world face three major issues associated with their aging societies: a declining population, an increasing proportion of seniors, and an increasing number of single-person households. To explore assistive technologies that can help solve the problems faced by aging societies, we have tested several information and robot technologies. This paper introduces research on a home-assistant robot, which improves the ease and productivity of home activities. For people who work hard outside the home, the assistant robot performs chores in their home environment while they are away. A case study of a life-sized robot with a humanlike functional body performing daily chores is presented. An integrated software system incorporating modeling, recognition, and manipulation skills, as well as a motion generation approach based on the software system, is explained. Moreover, because housekeepers perform chores one after another in their daily environment, we also aim to develop a system for continuously performing a series of tasks by including failure detection and recovery.

A grasp planning for picking up an unknown object for a mobile manipulator

This paper describes a grasp planning for a mobile manipulator which works in real environment. Mobile robot studies up to now that manipulate an object in real world practically use ID tag on an object or an object model which is given to the robot in advance. The authors aim to develop a mobile manipulator that can acquire an object model through video images and can manipulate the object. In this approach, the robot can manipulate an unknown object autonomously. A grasp planning proposed in this paper can find a stable grasp pose from the automatically generated model which contains redundant data and the shape error of the object. Experiments show the effectiveness of the proposed method

3-D object modeling by a camera equipped on a mobile robot

This paper describes 3-D shape modeling performed by a mobile robot. We propose a method in which the robot in the real environment acquires the accurate shape and constructs a 3-D model of an object using Computer Vision techniques under the condition that position and shape of the object is unknown. 3-D modeling is performed from image streams which are captured by a camera placed on the robot. The results show the effectiveness of our method.

System integration of a daily assistive robot and its application to tidying and cleaning rooms

This paper describes a software system integration of daily assistive robots. Several tasks related to cleaning and tidying up rooms are focused on. Recognition and motion generation functions needed to perform daily assistance are developed, and these functions are used to design various behaviors involved in daily assistance. In our approach, the robot behaviours are divided into simple units which consist of 3 functions as check/plan/do, it provides us with high reusable and flexible development environment. Because sequential task execution can be achieved only after functions about failure detection and recovery, we also try to implement such functions in keeping with this approach. In addition to using simple behavior unit, multilayer error handling is effective. Experiments doing several daily tasks with handling daily tools showed the effectiveness of our system.

Bottom dressing by a life-sized humanoid robot provided failure detection and recovery functions

This paper describes dressing assistance by an autonomous robot. We especially focus on a dressing action that is particularly problematic for disabled people: the pulling of a bottom along the legs. To avoid injuring the subjects legs, the robot should recognize the state of the manipulated clothing. Therefore, while handling the clothing, the robot is supplied with both visual and force sensory information. Based on the them, dressing failure is detected and recovery from the failure is planned automatically. The effectiveness of the proposed approach is implemented and validated in a life-sized humanoid robot.

Recognition and manipulation integration for a daily assistive robot working on kitchen environments

This paper describes a system integration of a daily assistive robot. Several tasks on cooking are focused on, recognition and manipulation functions are developed and integrated. It is often the case that kitchen tools and foods have less distinctive texture on its surface, and kitchen environments which are made of reflective materials are susceptible to the effect of illumination. From these fact, recognition functions are implemented with a basic policy which composes simple image features. On the other hand, tasks on kitchen often include relatively complicate dual arm manipulation. In such case it is effective in generating a robot pose by considering several manipulators at the same time. Experiments doing several cooking tasks with handling daily tools showed the effectiveness of our system.

Clothing classification using image features derived from clothing fabrics, wrinkles and cloth overlaps

This paper describes about a method of clothing classification using a single image. The method assumes to be used for building autonomous systems, with the purpose of recognizing day-to-day clothing thrown casually. A set of Gabor filters is applied to an input image, and then several image features that are invariant to translation, rotation and scale are generated. In this paper, we propose the descriptions of the features with focusing on clothing fabrics, wrinkles and cloth overlaps. Experiments of state description and classification using real clothing show the effectiveness of the proposed method.

Motion Planning for a Mobile Manipultor Based on Joint Motions for Error Recovery

This paper describes motion planning for a mobile manipulator which works in real environment. Mobile manipulators that can manipulate an object was developed up to now. We assume that object grasping is not restricted to just one grasp way and robot can move freely as far as it is in its operational area of the object. This paper proposes the motion planning for object grasping under the previous explained conditions. There are two major issues to detect the robot pose. The first problem is pose error of the robot hand. The second problem is kinematical redundancy of the mobile manipulator. The pose is evaluated from the amount of joint motions for recovery of hand pose error. Experiments show the effectiveness of the proposed method.

Picking up an Unknown Object through Autonomous Modeling and Grasp Planning by a Mobile Manipulator

This paper describes a novel framework for object picking and carrying task by a mobile manipulator. Conventionally, researches on mobile manipulator cope well with object manipulation task with utilizing predefined knowledge or specific tools. So these researches have an essential problem that a new target object cannot be added without relatively many preparation. On the other hand, in our framework of a robot system, because the robot can create the 3D shape model of the object and can plan a grasp pose for the object autonomously under the condition that only the position of the object is given to the robot. Experimental results show the effectiveness of our robot system to be implemented our proposed method.

Object shape reconstruction and pose estimation by a camera mounted on a mobile robot

This paper describes how to acquire 3-D shape of an object and to estimate robot pose by observing an unknown object. A single camera is placed on the robot, image streams of the target object are captured by the camera on a mobile robot moving around the object. Computer vision techniques are utilized under the condition that shape, size and accurate position information of the target object is not given in advance, but the robot finds the target object and reconstructs the 3-D object shape by itself. In addition, it is necessary that the robot grasps relative pose between itself and the target object. Experimental result show the effectiveness of our method in point of robustness and accuracy for the mobile robot.