Details of a Researcher - Takahashi, Masaki

Papers - Takahashi, Masaki

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Harmonious Robot Navigation Strategies for Pedestrians

Nakaoka S., Yorozu A., Takahashi M.

Lecture Notes in Networks and Systems (Lecture Notes in Networks and Systems) 412 LNNS 98 - 108 2022

ISSN 23673370

Recently, the demand for service robots that move autonomously in a crowded environment, such as stations, airports, and commercial facilities has increased. Such robots are required to move to a destination without hindering the progress of the surrounding pedestrians. Previous papers proposed collision avoidance methods based on the direction and distance of the destination of the robot, and the position and velocity of pedestrians in the vicinity. However, in a crowded environment, the behavior of a robot may affect other pedestrians, or the behavior of a pedestrian facing the robot may affect other pedestrians. Moreover, considering the motion strategy used by a pedestrian in a crowded environment, the impact on other pedestrians can be reduced by the robot following the pedestrians moving in the direction in which the robot wants to move. This navigation method has not been proposed thus far. Therefore, in this paper, we propose a method that considers the impact of the robot on surrounding pedestrians and the impact of those pedestrians on other pedestrians. The robot determines the avoidance or following action based on the traveling direction of the surrounding pedestrians.

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Human-Following Control in Furrow For Agricultural Support Robot

Yorozu A., Ishigami G., Takahashi M.

Lecture Notes in Networks and Systems (Lecture Notes in Networks and Systems) 412 LNNS 155 - 164 2022

ISSN 23673370

In Japan, the reduction in agricultural work population and increase in abandoned cultivated land are major social issues. To overcome these issues, we have proposed a small agricultural robot that supports the transportation of harvested crops while it follows the user. To move in the furrowed field, ridges and furrows where the robot can move must be detected using robot-mounted sensors and follow the ridge while avoiding the ridges and crop rows. However, when the robot follows the user ahead of it, it has difficulty detecting the ridges because of occlusion by the user. In addition, the robot requires to follow the user and move in and out of furrows of different widths in the farm field. To achieve smooth and safe harvesting support in the field with different width furrows, we propose a method for ridge detection and tracking by measuring the furrow width and interpolation using an RGB-D camera and a method for human-following control while avoiding ridges according to the ridge observation state using fuzzy set theory. To verify the proposed methods, experiments in the farm are carried out.

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Introduction of Damping Control for Obstacle Avoidance in Direct-Contact Cobotics Operations

Huart A., Yorozu A., Takahashi M.

Lecture Notes in Networks and Systems (Lecture Notes in Networks and Systems) 412 LNNS 506 - 517 2022

ISSN 23673370

In this study, obstacle avoidance in the collaborative robotics field, where a human operator moves the robot manually through direct contact, is investigated. If an operator is distracted or is not used to control the robot, an accident can happen during operation, which might harm the operator. For the purpose of assisting the human operator in his/her task, the integration of a damping control is proposed. Damping is a coefficient that influences the oscillations of a system. By modifying the damping of the robot, an artificial stiffness is created. The information is transmitted to the user through his/her haptic return, making it easier for him/her to avoid the obstacles in the workspace. In this study, a damping control is developed and implemented. Then, through experimentation, the efficiency of the haptic sense and the general damping control are demonstrated, and thus, an efficient, comfortable, and safe method is formulated for the operator to avoid obstacles during operations.

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Mobile Robot Localization Considering the Attributes of Objects to Prevent the Kidnapped Robot Problem

Harada T., Yorozu A., Takahashi M.

Lecture Notes in Networks and Systems (Lecture Notes in Networks and Systems) 412 LNNS 41 - 53 2022

ISSN 23673370

To prevent the occurrence of the kidnapped robot problem, it is vital to evaluate the likelihood of each particle considering an environmental change. Moving objects are one of the leading causes of environmental change, and each object has its own movability. For example, a chair has high movability because it is designed to move and often interacts with humans. However, walls or shelves have low movability because they are designed not to move, and they interact less often with humans. Therefore, in this study, we define classes of objects and their movability. We propose a localization approach that focuses on the association between sensor information obtained from objects whose movability is low and prior map by considering classes and movability, to prevent the occurrence of the kidnapped robot problem.

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Topometric Navigation Considering Movable Objects

Mochizuki S., Yorozu A., Takahashi M.

Lecture Notes in Networks and Systems (Lecture Notes in Networks and Systems) 412 LNNS 87 - 97 2022

ISSN 23673370

Recently, the demand for mobile manipulator-type human support robots has been increasing. Human support robots recognize the surrounding environment using a previously generated environmental map and perform navigation, such as localization and path planning. Conventional environment maps do not consider characteristics of objects and do not have any option to move an object to clear a path making it difficult for robots to move efficiently when an object is placed on their path. In this study, we propose topological navigation that uses a topological map based on sensing information and representing a path that robots can pass, and a metric map based on geometrical information of objects and representing the presence of objects. Consequently, if necessary, it is possible for robots to move a movable object to clear the passage and realize efficient movement in living environments.

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PROPOSAL OF AMD CONTROL METHOD BASED ON MODEL PREDICTIVE CONTROL FOR BMD VIBRATION CONTROL STRUCTURE AND VERIFICATION WITH SHAKING TABLE TEST

Yoshida N., Kotsuki S., Morikawa K., Kambara H., Fukukita A., Takahashi M.

Journal of Structural and Construction Engineering (Journal of Structural and Construction Engineering) 87 ( 798 ) 701 - 712 2022

ISSN 13404202

This paper proposes a control method of Active Mass Damper (AMD) for Building Mass Damper (BMD). The parameters of the soft story of BMD must be higher than the optimal values to prevent excessive displacement of the soft story. The AMD makes the behavior of the non-optimal BMD close to that of the optimal BMD and improves damping performance by the proposed control method, which is based on Model Predictive Control (MPC). Through the results of numerical analysis and shaking table test, it is demonstrated that the proposed method can mitigate the responses of the non-optimal BMD.

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World State-dependent Action Graph: A Representation of Action Possibility and Its Variations in Real Space based on World State

Kawasaki Y., Takahashi M.

Proceedings of the International Conference on Informatics in Control, Automation and Robotics (Proceedings of the International Conference on Informatics in Control, Automation and Robotics) 1 459 - 466 2022

ISSN 21842809

For intelligent systems, it is important to understand the action possibility for agent in real space. As the action possibility varies with the subsystem configuration of the agent and its states, the possibilities should be understood based on the world state comprising the agent’s state as well as the environmental state. However, most conventional methods consider only the environmental state. Therefore, this study proposes a world state-dependent action graph based on knowledge representation using scene graphs which allows the capturing of the action possibility of agents, which implies the feasible actions and their positions in real space, and their recursive variations depending on the world state. Moreover, the effectiveness of the proposed method was verified with simulations, assuming a coffee shop environment.

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UnrealEgo: A New Dataset for Robust Egocentric 3D Human Motion Capture

Akada H., Wang J., Shimada S., Takahashi M., Theobalt C., Golyanik V.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)) 13666 LNCS 1 - 17 2022

ISSN 03029743

We present UnrealEgo, i.e., a new large-scale naturalistic dataset for egocentric 3D human pose estimation. UnrealEgo is based on an advanced concept of eyeglasses equipped with two fisheye cameras that can be used in unconstrained environments. We design their virtual prototype and attach them to 3D human models for stereo view capture. We next generate a large corpus of human motions. As a consequence, UnrealEgo is the first dataset to provide in-the-wild stereo images with the largest variety of motions among existing egocentric datasets. Furthermore, we propose a new benchmark method with a simple but effective idea of devising a 2D keypoint estimation module for stereo inputs to improve 3D human pose estimation. The extensive experiments show that our approach outperforms the previous state-of-the-art methods qualitatively and quantitatively. UnrealEgo and our source codes are available on our project web page (https://4dqv.mpi-inf.mpg.de/UnrealEgo/ ).

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Spatio-Temporal Action Order Representation for Mobile Manipulation Planning

Kawasaki Y., Takahashi M.

RO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication: Social, Asocial, and Antisocial Robots (RO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication: Social, Asocial, and Antisocial Robots) 1093 - 1098 2022

Social robots are used to perform mobile manipulation tasks, such as tidying up and carrying, based on instructions provided by humans. A mobile manipulation planner, which is used to exploit the robot's functions, requires a better understanding of the feasible actions in real space based on the robot's subsystem configuration and the object placement in the environment. This study aims to realize a mobile manipulation planner considering the world state, which consists of the robot state (subsystem configuration and their state) required to exploit the robot's functions. In this paper, this study proposes a novel environmental representation called a world state-dependent action graph (WDAG). The WDAG represents the spatial and temporal order of feasible actions based on the world state by adopting the knowledge representation with scene graphs and a recursive multilayered graph structure. The study also proposes a mobile manipulation planning method using the WDAG. The planner enables the derivation of many effective action sequences to accomplish the given tasks based on an exhaustive understanding of the spatial and temporal connections of actions. The effectiveness of the proposed method is evaluated through practical machine experiments performed. The experimental result demonstrates that the proposed method facilitates the effective utilization of the robot's functions.

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Space Lander Descent Control System Design Considering Fuel Sloshing Under Microgravity

Tanaka Y., Baba M., Otsuki M., Fujita K., Himeno T., Maeda T., Takahashi M.

Proceedings of the IEEE Conference on Decision and Control (Proceedings of the IEEE Conference on Decision and Control) 2022-December 3092 - 3097 2022

ISSN 07431546

This study proposes a descent control system for a space lander with a large amount of fuel, to protect the lander from overturning when landing on microgravity objects. As sloshing is a major problem during descent, it is desirable to construct a control system that considers the sloshing dynamics. We derive a model of the lander considering fuel dynamics, determine the fuel-optimal trajectory for guidance, design a fuel state estimator for navigation, and design a tracking controller. The effectiveness of the proposed method is evaluated using a physical simulator. The proposed method achieves simultaneous stabilization of the lander and fuel, and is shown to be effective in preventing overturning.

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Simultaneous Optimization of Task Allocation and Path Planning Using Mixed-Integer Programming for Time and Capacity Constrained Multi-Agent Pickup and Delivery

Okubo T., Takahashi M.

International Conference on Control, Automation and Systems (International Conference on Control, Automation and Systems) 2022-November 1088 - 1093 2022

ISSN 15987833

Lately, there has been a need to improve the efficiency of material movements within factories and multi-agents are required to perform these tasks. In this study, graphical representation and mixed-integer programming have been adopted for simultaneous optimization of task allocation and path planning for each agent to achieve the following three goals. First, this study realizes time and capacity constrained multi-agent pickup and delivery (TCMAPD) that simultaneously considers time constraints, capacity constraints, and collision avoidance. Previous studies have not considered these constraints simultaneously. Thus, we can solve the problems associated with using multi-agents in actual factories. Second, we achieved TCMAPD that optimizes the collision avoidance between multi-agents. In conventional research, only a single collision avoidance method can be used. However, an appropriate route was selected from a variety of avoidance methods in this study. Hence, we could achieve a more efficient task allocation and path planning with collision avoidance. Third, the proposed method simultaneously optimizes task allocation and path planning for each agent. Previous studies have separately considered the approach of optimizing task allocation and path planning or used the cost of path planning after task allocation to again perform task allocation and path planning. To simultaneously optimize them in a single plan, we have developed a solution-derivable formulation using mixed-integer programming to derive a globally optimal solution. This enables efficient planning with a reduced total time traveled by the agents.

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ProTAMP: Probabilistic Task and Motion Planning Considering Human Action for Harmonious Collaboration

Mochizuki S., Kawasaki Y., Takahashi M.

IEEE International Conference on Intelligent Robots and Systems (IEEE International Conference on Intelligent Robots and Systems) 2022-October 2159 - 2166 2022

ISSN 21530858

For the proper functioning of mobile manipulator-type autonomous robot performing complicated tasks in a human-robot coexistence environment, tasks and motions must be planned simultaneously. In such environments, a human and robot should collaborate with each other. Therefore, the robot must act in accordance with the human and avoid useless actions duplicated with those of humans. However, any action undertaken by a human has uncertainty, and thus, predicting them correctly is challenging. This study proposed probabilistic task and motion planning considering both deterministic and probabilistic environment changes caused by robot and human actions temporarily and spatially, respectively. First, the environmental changes were modeled, where the robot is capable of recognizing the possibility of environmental changes. Second, in task planning, the probabilities of each environmental change owing to human actions was minimized. Finally, in motion planning, a movement path connecting each task in a planned order was planned, thereby enabling the robot to perform actions not duplicated with those by a human. Furthermore, the plans generated were compared without considering possibility of human actions and the effectiveness of the proposed method was verified. Consequently, the proposed method was confirmed to reduce the time required for finishing the tasks.

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Image-based Action Generation Method using State Prediction and Cost Estimation Learning

Ishihara Y., Takahashi M.

Journal of Intelligent and Robotic Systems: Theory and Applications (Journal of Intelligent and Robotic Systems: Theory and Applications) 103 ( 1 ) 2021.09

ISSN 09210296

This study proposes an image-based action generation method using a controller that is trained with experiences autonomously collected by a robot. Operating a robot using its state or point in coordinate space is not always easy for human operators to control. This is because humans do not interpret the world as a coordinate space. Depending on the task, inputs such as voice-input or image-input are easier for human operators to use when managing a robot. Accordingly, we studied an image-based control method of robotic agents. Designing an image-based controller by hand for different tasks and input images is highly complex. Therefore, a controller which can be automatically trained from experiences collected by a robot is strongly preferred. In addition, when considering the operation of a robot in a real environment, the controller should guarantee the safety of a robot’s behavior in a way that is configurable and understandable by the human operator. However, most previous approaches trained the controller end-to-end, which does not guarantee the safety of the behavior learned by the controller. Instead of training the controller end-to-end, we train state prediction and cost estimation functions to solve the action generation as a path planning problem. By doing so, we can explicitly design and specify the undesired state of a robot in the configuration space. The results show that the proposed method can be used to provide safe navigation to different goal positions in a realistic living room-like environment with an hour of training data.

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Footsteps and walking trajectories during the Timed Up and Go test in young, older, and Parkinson's disease subjects

Okada Y., Yorozu A., Fukumoto T., Morioka S., Shomoto K., Aoyama T., Takahashi M.

Gait and Posture (Gait and Posture) 89 54 - 60 2021.09

ISSN 09666362

Background: Footsteps and walking trajectories during the Timed Up and Go test (TUG), and their relationships with spatiotemporal gait parameters during turning in people with Parkinson's disease (PD) and older people have not been clarified. Research question: We investigated the footsteps, walking trajectories, and spatiotemporal parameters during the TUG in PD, healthy older (HO), and healthy young (HY) subjects and the associations between the parameters of footsteps or walking trajectories and the spatiotemporal parameters during turning. Methods: Twenty-six PD, 20 HO, and 20 HY subjects participated. They performed the TUG at self-selected speed and underwent evaluations of spatiotemporal parameters in the forward, turning, and return phases and parameters of footsteps and walking trajectories by a system using laser range sensors to measure the two-dimensional distance data of the legs. Foot placement for each foot was measured as the estimated position when the leg speed of movement reached the minimum between foot-contact and foot-off. We calculated the minimum distance from a TUG marker to footsteps and the maximum anterior distance from the start to the footsteps. Step length was calculated using a method for non-linear walking. Results: The PD subjects showed significantly smaller step lengths in all phases. The minimum distance from the marker to the footsteps in PD subjects was significantly smaller than in HO subjects and was significantly positively correlated only with the turning-phase step length. The maximum anterior distance from the start to footsteps in HO subjects was significantly larger than in PD and HY subjects and was not correlated with any spatiotemporal parameters. Significance: This study demonstrated that people with PD turn close to the TUG marker, and this turning strategy may be associated with the decreased step length when turning. These findings could help in providing instructions which prevent the exaggeration of step-length reduction when turning.

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Microcurrent Therapy as a Therapeutic Modality for Musculoskeletal Pain: A Systematic Review Accelerating the Translation From Clinical Trials to Patient Care

Iijima H., Takahashi M.

Archives of Rehabilitation Research and Clinical Translation (Archives of Rehabilitation Research and Clinical Translation) 3 ( 3 ) 2021.09

Objective: To summarize the level of knowledge regarding the effects of microcurrent therapy (MCT) on musculoskeletal pain in adults. Data Sources: The PubMed, Physiotherapy Evidence Database, Cumulative Index to Nursing Allied Health Literature, Cochrane Central Register of Controlled Trials, and Igaku Chuo Zasshi database were searched from the time of their inception to December 2020. Study Selection: Randomized controlled trials (RCTs) investigating the effects of MCT on musculoskeletal pain were included. Additionally, non-RCTs were included to assess the adverse events. Data Extraction: The primary outcomes were pain and adverse events related to MCT. To assess the reproducibility of MCT, we evaluated the completeness of treatment description using the Template for Intervention Description and Replication (TIDieR) checklist. We also assessed the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Data Synthesis: A comprehensive assessment of 4 RCTs and 5 non-RCTs that met the inclusion criteria revealed that MCT significantly improved shoulder pain (1 study, 40 patients) and knee pain (1 study, 52 patients) compared with sham MCT without any severe adverse events. MCT has clinically significant benefits for knee pain. This study also revealed a clinically significant placebo response in treating knee pain. This evidence highlights the substantial effect of placebo response in clinical care. These treatment effects on knee pain are further supported by the high quality of evidence in GRADE with high reproducibility in TIDieR. Conclusions: The findings of this meta-analysis highlight the effect of placebo response in treating knee pain. MCT is a potential, core nonpharmacologic treatment option in clinical care with minimal adverse events and should be further investigated. This study proposes a framework for the future investigation of the effect of MCT on musculoskeletal pain to enhance the study quality and reproducibility.

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Staircase design for health monitoring in elderly people

Ogawa A., Iijima H., Takahashi M.

Journal of Building Engineering (Journal of Building Engineering) 37 2021.05

The need for early detection and intervention for age-related health deterioration via home-based health monitoring systems is growing with global population aging. Health deterioration is typically evaluated using questionnaires, but obtaining frequent responses is difficult. Although stair walking involving a high physical load is suitable for assessing health deterioration, uniform assessment using home-based systems is difficult because different stair designs result in different movements. There is currently insufficient research on differences in evaluation performance between different stair designs. The current study aimed to develop an objective index to assess difficulties in activities of daily living (ADLs) as an indicator of health deterioration by observing stair walking, and to investigate the effects of stair dimensions on the relationship between the index and health deterioration. We hypothesized that knee joint positions during stair ascent would be associated with health deterioration, and developed the “Stepping in Level” index, reflecting the knee joint position when stepping in, obtained using a markerless depth information-based system. Seventy elderly people ascended two types of stairs (steep: 33.7°; shallow: 28.2°) and completed a questionnaire regarding ADL difficulty. We used a generalized linear mixed model to investigate the ability of “Stepping in Level” to explain ADL difficulty. The results revealed that “Stepping in Level” was able to explain ADL difficulty, and steep stairs were more suitable than shallow stairs for assessment. Our system enables daily assessment of difficulty in ADLs and detection of subtle changes in daily life. The current findings could inform design guidelines for health monitoring.

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Low Back Pain as a Risk Factor for Recurrent Falls in People With Knee Osteoarthritis

Iijima H., Shimoura K., Aoyama T., Takahashi M.

Arthritis Care and Research (Arthritis Care and Research) 73 ( 3 ) 328 - 335 2021.03

ISSN 2151464X

Objective: Knee osteoarthritis (OA) has been suggested to increase the risk of falls. Low back pain (LBP) is a potential risk factor for falls in people with knee OA, but this issue has not been addressed adequately in previous studies. The objective of this study was to investigate the relationship between LBP and falls in people with knee OA in a 12-month period. Methods: Participants with knee OA (Kellgren/Lawrence [K/L] grade ≥1) completed questionnaires for LBP and falls that occurred in the preceding 12 months. Binary and ordinal logistic regression analyses were performed to assess the relationship between LBP or moderate-to-severe LBP (numeric rating scale ≥4 points) and any fall (≥1 fall) or recurrent falls (≥2 falls) after adjustment for age, sex, K/L grade, knee pain severity, and quadriceps strength. Sensitivity analyses were performed excluding people with sciatica, nonchronic LBP, K/L grade 1, and those receiving pain medications. Results: We included 189 participants (ages 61–90 years, 78.3% women) in this study. Of these participants, 41 (21.6%) reported falls in the preceding 12 months. People with any LBP (n = 101) and those with moderate-to-severe LBP (n = 45) had 2.7- and 3.7-times higher odds of recurrent falls, respectively. Sensitivity analyses revealed a strong correlation between moderate-to-severe LBP and recurrent falls. Conclusion: Thorough investigation of LBP as a risk factor for recurrent falls in people with knee OA may provide a novel insight into the pathomechanics of recurrent falls in this population.

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Bottom-up action modeling via spatial factorization for serving food

Kawasaki Y., Takahashi M.

Advanced Robotics (Advanced Robotics) 35 ( 12 ) 756 - 770 2021

ISSN 01691864

The goal state of the robot motion involved in an action is determined by the action model based on the effect of the action and the scene state. This study focuses on serving food as a robot action; the action model of serving food is obtained based on demonstrations. The arrangement position is determined by considering the spatial relations between the object being served and the multiple selected reference objects. Therefore, it is necessary to learn the importance of the relations for the reference and the spatial relations between objects based on demonstrations. In this paper, bottom-up action modeling is proposed as an action modeling approach based on the demonstration. In this method, the spatial relations between labeled objects and the importance of the relations are learned through spatial factorization of the scene into partial relations. This approach enables the robot to determine the arrangement position intended by the demonstrator, even in unknown scenes. The effectiveness of the proposed method was evaluated by simulation, which the action of serving food.

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Body pressure prediction for pressure ulcer prevention in a bed head elevation operation

Kosuge M., Ishihara Y., Takahashi M.

Advanced Robotics (Advanced Robotics) 35 ( 3-4 ) 181 - 193 2021

ISSN 01691864

Pressure ulcers are caused by tissue damage, which occurs when the blood supply to an area of skin is diminished because of sustained or concentrated pressure on a patient from the mattresses of a bed. One action that concentrates the pressure is a bed head elevation operation. Recently, a control system known as the alternative pressure mattress has been proposed to prevent the concentration of pressure. However, the challenge with this controlled system is that it has a slow response because it uses air cells. The slow response causes controlling the air cells to lag behind the change in pressure during the bed head elevation operation. Therefore, this system cannot adequately prevent the concentration of pressure on a patient. To address this issue, we need to predict the change in pressure during the bed head elevation operation and control the pressure based on this prediction. In the current work, we focus on predicting the pressure distribution. This prediction is high-dimensional. We regarded the pressure distribution as an image and predicted the change in pressure by applying a deep neural network. To the best of our knowledge, this paper is the first to propose the body pressure predictive model.

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ASTRON: Action-Based Spatio-Temporal Robot Navigation

Kawasaki Y., Mochizuki S., Takahashi M.

IEEE Access (IEEE Access) 9 141709 - 141724 2021

To achieve the tasks provided by a user, it is necessary for robots to have a plan that fully exploits their functionalities in an environment. The objective of this study is to realize robot task planning in real space for effectively use of the robot's functions The plan is formed by deriving a feasible action sequence by interpreting the instructions within the scope of the action possibilities of the robots and the changes in them. In this paper, we first propose an action graph as a novel environmental representation approach to facilitate the understanding of the robot's action possibility in real space. In the action graph, the action possibility is represented by nodes, which describe the spatial position to perform each feasible action, and edges, which describe the feasible actions, based on the subsystem-level affordance and the arrangement of objects in the environment. We also propose an action-based spatio-temporal robot navigation (ASTRON), which focuses on robot navigation tasks. ASTRON enables the robots to determine a feasible action sequence that utilizes their functions by interpreting the instructions based on the action graph. The effectiveness of the proposed method was evaluated through simulations and actual machine experiments in a coffee shop environment. In the actual machine experiments, the proposed method was applied to robots with different subsystem configurations. The experimental results demonstrated that the proposed method could plan the feasible action sequence to complete the tasks by considering the environmental state and the subsystem configurations of the robot.

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