In order to accurately reach a target position while executing a task which imposes occlusion or constraints of the posture, a humanoid robot requires an adaptive locomotion system, which can comprehensively integrate localization, environmental mapping, global locomotion planning and local error correction. In this paper, we propose a method of constructing a perception based locomotion system for a humanoid robot. The major contribution of this paper is solving a problem of the locomotion error caused by the task constraints, by locally compensating footsteps and assessing the need for global footstep re-planning online based on environmental measurements. The proposed system provides an accurate and dense ground point cloud, called HeightField, using plane estimation and space interpolation, and obstacle point cloud for frequent collision avoidance by accumulating laser scans. This environmental perception enables a humanoid robot to plan footsteps globally even in the situation where the sight of the robot is limited and compensate footsteps while estimating landing state during locomotion online with the localization result. We evaluated the practicality of the proposed system by applying it to our humanoid robot carrying a heavy object in a construction site and confirmed that the proposed system contributed to improved locomotion abilities of a humanoid robot engaging in heavy-duty or dangerous tasks.

This paper reports the results of a survey on introducing robots and other new technologies to care services, such as care for older adults. Demographic data show that the ratio of older adults in Japan has already exceeded 23.3%. Japan also is facing a severe shortage of the working-age population, which could lead to a reduction in the quality of care services for older adults; therefore, robots and the provision of new forms of information technologies are expected to be utilized in such care services. The purpose of this study is to help facilitate the introduction of novel technologies in care services, such as in long-term care facilities. We focus on information-related costs that are incurred prior to the purchase of technologies such as attending exhibitions and conducting Internet searches. This report shows the results of an investigation into such information-related costs for three different products, and discusses the importance of the appropriate management of information costs from the development phase through to the introduction phase of such products.

With the aging population trends in developed countries, there is an increased expectation of the application of assistive robots. A variety of robots have been developed to address this challenge. Although there are many technical problems to be solved, the lack of objective evaluation indexes for evaluating the benefit to the users is one of the important problems to be addressed before the commercialization of the assistive robots can be realized. The ICF (International Classification of Functioning, Disability and Health) is a classification of the health components of functioning and disability, and is being utilized in medical, healthcare, and welfare fields. The ICF has a basic framework to evaluate healthcare and welfare equipment, including robots, and it will be the basis of the evaluation indexes for assistive robots. In this paper, we present the development of evaluation indexes, and provide the results of preliminary experiments which were conducted using iARM and RAPUDA robots performing a certain lifting task. The experiments illustrate the issues involved in the development of ICF-based indexes for assitive robots.

In order to execute multiple tasks in offices and houses, robots require a large amount of information. If each item that is part of the ambience is endowed with some intelligence, robots can simply change the state of the item as requested by the item itself. We refer to such an ambience as “intelligent ambience (IA).” This paper describes a constitution method for designing an IA. We constructed two IA models - one comprised a drawer and a mobile robot and the other comprised two types of doors and a drawer, a device developed specially for this IA, and a humanoid robot. We also verified the effectiveness of the IA experimentally.

Abstract This paper deals with whole‐body motion planning and dynamic control for humanoid from two aspects: locomotion including manipulation and reaching. In the first part, we address a problem of simultaneous locomotion and manipulation planning that combines a geometric and kinematic motion planner with a dynamic humanoid motion generator. The second part deals with whole‐body reaching tasks by using a generalized inverse kinematics (IK) method to fully exploit the high redundancy of the humanoid robot. Through experiments using humanoid platform HRP‐2 No. 14 installed at LAAS‐CNRS, we first verify the validity of each method. An integrated experiment is then presented that unifies the both results via visual perception to execute an object‐fetching task. Copyright © 2009 John Wiley & Sons, Ltd.

Structuring methods of ambient intelligence are becoming important issue in robotics field; such ambient intelligence can enable robots to adopt ubiquitous computing technologies by using GPS and the RFID tag, acquire the necessary information for working in offices and houses, and thereby work accordingly. There are two merits in putting information into an environment. Firstly, persons who develop each robot can minimize the installation of knowledge of the objects that the robot may use. The new knowledge of the objects are provided by the manufacturers of the object and the owners, designers, architects, or removers who structure the environment whenever the ambience changes. Secondly, in case of different robots, the same ambient intelligence can handle different kinds of robots. No one needs to customize each robot. Each robot is able to execute tasks using the common ambient intelligence.

We propose a general and practical planning framework for generating 3-D collision-free motions that take complex robot dynamics into account. The framework consists of two stages that are applied iteratively. In the first stage, a collision-free path is obtained through efficient geometric and kinematic sampling-based motion planning. In the second stage, the path is transformed into dynamically executable robot trajectories by dedicated dynamic motion generators. In the proposed iterative method, those dynamic trajectories are sent back again to the first stage to check for collisions. Depending on the application, temporal or spatial reshaping methods are used to treat detected collisions. Temporal reshaping adjusts the velocity, whereas spatial reshaping deforms the path itself. We demonstrate the effectiveness of the proposed method through examples of a space manipulator with highly nonlinear dynamics and a humanoid robot executing dynamic manipulation and locomotion at the same time.

In this paper we address smooth and collision-free whole-body motion planning for humanoid robots. A two-stage iterative planning framework is introduced where geometric motion planner and dynamic pattern generator interacts by exchanging the trajectory, to obtain 3D whole-body dynamic motions simultaneous tasks including locomotion, in complex environments. We propose a practical method for smooth motion reshaping to avoid collisions in generated dynamic motion. Based on motion editing techniques in computer graphics animation, smooth collision-avoiding motion is generated through trajectory deformation. The validity of the proposed reshaping method is verified by computer simulations and experiments using humanoid platform HRP-2

This paper describes a preliminary study on a merging control algorithm of vehicles on highways using intervehicle communication. Merging control of a single vehicle into a platoon of vehicles is achieved by mapping of a vehicle onto a ramp or a main line to generate a virtual vehicle with which a vehicle is longitudinally controlled. Simulation studies show feasibility of the algorithm.

This paper discusses robot motion planning in dynamic environments, and especially generation of a motion pattern of a manipulator to achieve a task under restrictions of time and space. We focus on a game of "kendama" (Japanese ball-in-cup game) that requires such a task. We do not intend to make robots mimic the actions of human being, but we discuss robots acting based on outside sensory feedback signals. In the "kendama" task, the robot learns physical properties through trials, because no a priori knowledge of both the mass of the ball and the length of the string is available. This paper proposes a method to generate the motion pattern of the manipulator with a force sensing device attached to the end tip to perform the "kendama" task. Experimental results obtained using a two DOF direct-drive manipulator are also shown.>

Discusses robot motion planning in dynamic environment, that is, generation of a motion pattern to attain a working purpose. The authors examine the relation between this redundancy and the dynamic dexterity of robots. Especially the authors focus on 'juggling' as a typical example of such a working purpose(task). To juggle several balls in the gravitational field, the motion of the robot is determined considering the dynamic property of balls. It is shown that a parametric representation of the robot motion makes it easy to generate an appropriate trajectory of the end-effector for 'juggling task'.>