Personal Robots Research Articles

Posture Control for Personal Mobility Robot Using Feedback Compensation with Unstable Pole

SUMMARYThis paper presents a novel posture control approach using feedback compensation with an unstable pole. For a narrow and small personal mobility robot (PMR), this is needed in order to control its posture for achieving quick turning and high acceleration. However, in the conventional control approach that uses the posture angle as a controlled variable, the zero moment point (ZMP) does not settle to the desired point in the following cases: an unknown disturbance force given to the PMR, a fluctuation in the center of gravity of the PMR, and a change in the conditions between the tires and the road surface. In this paper, a novel control method using feedback compensation with an unstable pole is proposed to achieve the desired ZMP in the steady state. The proposed controller changes the control input for the actuator of posture control to zero in order to achieve the desired posture angle. The effectiveness of the proposed approach is verified through experiments using a prototype of the PMR.

Robots that Talk and Listen Judith A. Markowitz (editor) (President of J. Markowitz, Consultants, Chicago, IL) Berlin/Boston/Munich: Walter de Gruyter, 2015, hardbound, ISBN 978-1-61451-603-3; PDF, e-ISBN 978-1-61451-440-4 EPUB; e-ISBN 978-1-61451-915-7

<b>Robots that Talk and Listen</b> <b>Judith A. Markowitz (editor)</b> (President of J. Markowitz, Consultants, Chicago, IL) Berlin/Boston/Munich: Walter de Gruyter, 2015, hardbound, ISBN 978-1-61451-603-3; PDF, e-ISBN 978-1-61451-440-4 EPUB; e-ISBN 978-1-61451-915-7

노약자의 낙상가능지역 진입방지를 위한 보안로봇의 주행경로제어

One of the goals in the field of mobile robotics is the development of personal service robots for the elderly which behave in populated environments. In this paper, we describe a security robot system and ongoing research results that minimize the risk of the elderly and the infirm to access an area to enter restricted areas with high potential for falls, such as stairs, steps, and wet floors. The proposed robot system surveys a potential falling area with an equipped laser scanner sensor. When it detects walking in elderly or infirm patients who in restricted areas, the robot calculates the velocity vector, plans its own path to forestall the patient in order to prevent them from heading to the restricted area and starts to move along the estimated trajectory. The walking human is assumed to be a point-object and projected onto a scanning plane to form a geometrical constraint equation that provides position data of the human based on the kinematics of the mobile robot. While moving, the robot continues these processes in order to adapt to the changing situation. After arriving at an opposite position to the human's walking direction, the robot advises them to change course. The simulation and experimental results of estimating and tracking of the human in the wrong direction with the mobile robot are presented.

Learning preferences for manipulation tasks from online coactive feedback

We consider the problem of learning preferences over trajectories for mobile manipulators such as personal robots and assembly line robots. The preferences we learn are more intricate than simple geometric constraints on trajectories; they are rather governed by the surrounding context of various objects and human interactions in the environment. We propose a coactive online learning framework for teaching preferences in contextually rich environments. The key novelty of our approach lies in the type of feedback expected from the user: the human user does not need to demonstrate optimal trajectories as training data, but merely needs to iteratively provide trajectories that slightly improve over the trajectory currently proposed by the system. We argue that this coactive preference feedback can be more easily elicited than demonstrations of optimal trajectories. Nevertheless, theoretical regret bounds of our algorithm match the asymptotic rates of optimal trajectory algorithms. We implement our algorithm on two high-degree-of-freedom robots, PR2 and Baxter, and present three intuitive mechanisms for providing such incremental feedback. In our experimental evaluation we consider two context rich settings, household chores and grocery store checkout, and show that users are able to train the robot with just a few feedbacks (taking only a few minutes).

Speech Interaction with Personal Assistive Robots Supporting Aging at Home for Individuals with Alzheimer’s Disease

Increases in the prevalence of dementia and Alzheimer’s disease (AD) are a growing challenge in many nations where healthcare infrastructures are ill-prepared for the upcoming demand for personal caregiving. To help individuals with AD live at home for longer, we are developing a mobile robot, called ED, intended to assist with activities of daily living through visual monitoring and verbal prompts in cases of difficulty. In a series of experiments, we study speech-based interactions between ED and each of 10 older adults with AD as the latter complete daily tasks in a simulated home environment. Traditional automatic speech recognition is evaluated in this environment, along with rates of verbal behaviors that indicate confusion or trouble with the conversation. Analysis reveals that speech recognition remains a challenge in this setup, especially during household tasks with individuals with AD. Across the verbal behaviors that indicate confusion, older adults with AD are very likely to simply ignore the robot, which accounts for over 40% of all such behaviors when interacting with the robot. This work provides a baseline assessment of the types of technical and communicative challenges that will need to be overcome for robots to be used effectively in the home for speech-based assistance with daily living.

Natural Interaction with an Assistive Humanoid Robot

This paper addresses the concept of “natural interaction”, defined as a way to interact in a simple, human-like and intuitive manner with personal assistive robots. A human-robot interaction system was developed for this purpose in order to provide means for expert and non-expert users to cooperate and interact with an assistant humanoid robot (Nao) operating in a domestic environment, allowing them to express their instructions as combinations of gestures and speech inputs.

A signal pattern recognition approach for mobile devices and its application to braking state classification on robotic mobility devices

Personal Mobility Robots, such as the Seqway may be the remedy for the transportation related problems in the congested environment, especially for the last and first mile problems of the elderly people. However, the vehicle segmentation issues for the mobility robots, impede the use of these devices on the shared paths. The mobility reports can only be used in the designated areas and private facilities. The traffic regulatory institutions lack robot–society interaction database. In this study, we proposed methods and algorithms which can be employed on a widespread computing device, such as an Android tablet, to gather travel information and rider behavior making use of the motion and position sensors of the tablet PC. The methods we developed, first filter the noisy sensor readings using a complementary filter, then align the body coordinate system of the device to the Segway’s motion coordinate. A couple of state of the art classification methods are integrated to classify the braking states of the Segway. The classification algorithms are not limited to classification of the braking states, but they can be used for other motion related maneuvers on the road surfaces. The detected braking states and the other classified features related to the motion are reflected to the screen of the Android tablet to inform the rider about the riding and motion conditions. The developed Android application also gathers these travel information to build a National database for further statistical analysis of the robot–society interaction.

Building technology platform aimed to develop service robot with embedded personality and enhanced communication with social environment

The paper is addressed to prototyping of technology platform aimed to develop of ambient-aware human-centric indoor service robot with attributes of emotional intelligence to enhance interaction with social environment. The robot consists of a wheel-based mobile platform with spinal (segmented) torso, bi-manual manipulation system with multi-finger robot hands and robot head. Robot prototype was designed to see, hear, speak and use its multimodal interface for enhanced communication with humans. Robot is capable of demonstrating its affective and social behavior by using audio and video interface as well as body gestures. Robot is equipped with advanced perceptive system based on heterogeneous sensorial system, including laser range finder, ultrasonic distance sensors and proximity detectors, 3-axis inertial sensor (accelerometer and gyroscope), stereo vision system, 2 wide-range microphones, and 2 loudspeakers. The device is foreseen to operate autonomously but it may be also operated remotely from a host computer through wireless communication link as well as by use of a smart-phone based on advanced client-server architecture. Robot prototype has embedded attributes of artificial intelligence and utilizes advanced cognitive capabilities such as spatial reasoning, obstacle and collision avoidance, simultaneous localization and mapping, etc. Robot is designed in a manner to enable uploading of new or changing existing algorithms of emotional intelligence that should provide to robot human-like affective and social behavior. The key objective of the project presented in the paper regards to building advanced technology platform for research and development of personal robots aimed to use for different purpose, e.g. robot-entertainer, battler, robot for medical care, security robot, etc. In a word, the designed technology platform is expected to help in development human-centered service robots to be used at home, in the office, public institutions, etc.

Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

ABSTRACT For a domestic personal robot, personalized services are as important as predesigned tasks, because the robot needs to adjust the home state based on the operator's habits. An operator's habits are composed of cues, behaviors, and rewards. This article introduces behavioral footprints to describe the operator's behaviors in a house, and applies the inverse reinforcement learning technique to extract the operator's habits, represented by a reward function. We implemented the proposed approach with a mobile robot on indoor temperature adjustment, and compared this approach with a baseline method that recorded all the cues and behaviors of the operator. The result shows that the proposed approach allows the robot to reveal the operator's habits accurately and adjust the environment state accordingly.

離床アシストベッド「リショーネ&lt;sup&gt;®&lt;/sup&gt;」のISO 13482適合設計・評価

The International Organization for Standardization (ISO) has issued ISO 13482, which is a new global safety standard for personal care robots and is the key to these safety for human. However, it is a conceptual standard, which does not have concrete standard values. Moreover, when protective measures for risk reduction are implemented using the control system, it has to be developed based on functional safety standard, which is difficult to interpret. Therefore it is very difficult to understand concretely how to design and evaluate personal care robots in order to meet this standard. At such times, we acquired the certification of ISO 13482 in the robotic care equipment which is integration of an electric care bed and an electric reclining wheelchair. This paper reports a concrete example of how to develop and evaluate robotic care equipments based on ISO 13482.

An Approach of Safety for Personal Care Robots and Certification under ISO13482(Special Issue on Safety of Service Robots)

An Approach of Safety for Personal Care Robots and Certification under ISO13482(Special Issue on Safety of Service Robots)

パーソナルモビリティロボットの製作と実験特区への参加

パーソナルモビリティロボットの製作と実験特区への参加

Safety Standard for Personal Care Robot ISO 13482 and System Safety(Special Issue on Safety of Service Robots)

Safety Standard for Personal Care Robot ISO 13482 and System Safety(Special Issue on Safety of Service Robots)

モデル予測制御に基づくパーソナルロボットの姿勢安定化制御

モデル予測制御に基づくパーソナルロボットの姿勢安定化制御

ヒトを活動的にする移動支援ロボット

ヒトを活動的にする移動支援ロボット

2P1-M02 電磁場変動検出を利用したパーソナルロボットのユーザ追従システム

While seamless switching between the accompanying and handling modes for an outdoor personal robot is required, a lack of sensors that can robustly detect the proximity and touch of the user has hindered its practical development. In this study, a novel sensing technology using electromagnetic field fluctuation is presented. The experiment, using a suitcase with the sensor, showed that the area surrounding the user, as well as the direct touch of the user can be separately detected. We also embedded the system into the robotic suitcase and showed that the robot can robustly follow the users.

Study of Charged Frame ESD Immunity Testing Specified in ISO 7176-21

The EMC product standard for electrically powered wheelchairs is ISO 7176-21, which requires charged frame electrostatic discharge (ESD) immunity testing. When a moving wheelchair carrying a buildup of electrostatic charge due to triboelectrification of the wheels and floor comes into contact with a grounded metal object, the resulting air-gap discharge may cause the wheelchair to malfunction. Since the IEC 61000-4 series does not cover immunity testing that simulates such ESD events, ISO 7176-21 independently provides the test method. Currently, many companies are developing personal care robots to assist human in daily activities. Considering the risk presented by such robots that involve physical contact with humans, the charged frame ESD test will be a test item for the safety validation of personal care robots that are mobile and battery powered. In practice, however, when charged frame ESD tests are conducted according to the test procedure specified in ISO 7176-21, some issues and questions arise in regard to such matters as the means of charging the robot under test, the material of the insulating support on which to place the robot, and simulation of discharge from a robot rider or wearer. This paper investigates the test procedure of ISO 7176-21 and proposes modifications for enabling charged frame ESD testing to be properly carried out for personal care robots.

Hybrid therapy of walking with Kinesis overground robot for persons with incomplete spinal cord injury: A feasibility study

Rehabilitation of walking ability is one of the most important objectives after a spinal cord injury. Robotic and neuroprosthetic technologies hold a considerable potential for driving walking rehabilitation therapies. However, new developments are needed in order to improve the walking rehabilitation interventions based in these technologies.We recently presented a cooperative control strategy of Kinesis, a lower limb exoskeleton for providing hybrid therapy of walking (Del-Ama, 2014). Its design aimed to actively manage muscle fatigue caused by surface electrical stimulation, and to implement the assist-as-needed control paradigm in which both stimulation and robotic controller cooperate with the residual functionality of the user. In this article we present three case studies for investigating the feasibility of the hybrid therapy of walking delivered with Kinesis in patients with incomplete spinal cord injury. Besides, the adaptability features of Kinesis stimulation–robot cooperative control are assessed, characterizing the behavior of the cooperative controller while providing hybrid therapy of walking.Patients with incomplete spinal cord injury participated in the experiments. The protocol consisted of walking with Kinesis during 6 min. Three configurations of the cooperative controller were tested for each patient in separate sessions in order to investigate its adaptability features. The immediate impact of the hybrid therapy of walking was assessed through several variables that represent the physiological impact, user–exoskeleton physical interaction, stimulation intensity and user subjective perception of the hybrid therapy of walking.Results show that the cooperative controller of Kinesis adapted to patient functional deficits and voluntary actions during walking, modulating stimulation and robotic assistance, which was the aim of the controller design. Nevertheless, no noticeable differences were observed in the comparison between compliant and trajectory exoskeleton control. Further work is envisioned regarding several aspects of hybrid walking control: stimulation control based on muscle activation estimate, improved semi-automatic control of walking, and improved muscle fatigue monitoring. The hybrid walking therapy was tolerated by the patients without adverse effects, along with a tolerable physical demand. This shows a potential for walking rehabilitation in motor incomplete SCI patients, guaranteeing further research on this topic.

Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots.

Development of a Personal Mobility Robot “NENA”

&lt;div class=""abs_img""&gt;&lt;img src=""[disp_template_path]/JRM/abst-image/00260005/16.jpg"" width=""300"" /&gt;NENA and experiments in Tsukuba&lt;/div&gt; A mobility robot “NENA” which can carry one person was developed by Utsunomiya University. The robot was developed based on the concept called “Design Framework” and it allowed the robot to equip with functions needed for manual driving and autonomous running and acceptable design for people. The robot fulfilled safety required for mobility robots used in the Tsukuba Mobility Robot Experimental Zone. &lt;/span&gt;