Reviewerly/exHarmony huggingface dataset:
Tcl-based Simulation Platform for Light-weight ResNet Implementation

The growing computational cost and size of artificial intelligence have led to a need for hardware accelerators. However, training times for neural networks remain a significant obstacle, leading to increased simulation times and decreased productivity. In this paper, we propose a runtime layer replaceable simulation platform using a depth-reduction algorithm. The proposed platform generates weights optimized for various ResNet depths using the first trained high-depth weights. This platform can reduce simulation time by reducing the number of trainings without significantly degrading the inference accuracy. As a result of the depth reduction simulation using the MNIST data set, the accuracy was over 97% when the number of layers was reduced to less than 71%
A High-Performance YOLOV5 Accelerator for Object Detection with Near Sensor Intelligence

Object detection is widely used in fields such as intelligent surveillance and autonomous driving. Currently, object detection algorithms based on convolutional neural networks have achieved significant performance improvements. However, due to the complexity of the algorithms and computational constraints, it is challenging to deploy them on edge computing platforms to achieve near sensor intelligence. Therefore, we have optimized and quantized the lightweight Yolov5s model to obtain a hardware-friendly Q-Yolov5s. We propose a high-performance accelerator based on the hybrid streaming architecture. The experimental results on the AX7350 FPGA show that the throughput and energy efficiency of the accelerator are 10.80 GOPs and 78.62 Pixels/mJ, respectively. Compared with the existing work, the increases are 85.25% and 35.41%, respectively. And the energy efficiency of the accelerator is 2.0 and 2.2 times higher than that of Intel i7-12700 CPU and NVDIA RTX 3070 GPU, respectively. Therefore, it is more suitable for deploying on edge computing platforms to achieve near sensor intelligence.
A Model-Guided Underwater Image Enhancement Network

Underwater image enhancement is an important issue in many marine vision tasks. However, the existing model-based methods are difficult to always provide expected results for different scenes, while the heuristic data-driven neural networks generally involve complicated architectures to pursue desirable images. To deal with this dilemma, this paper introduces a framework for combining the power of model-based methods with data-driven neural networks to enhance the visibility of underwater images. This framework, termed model-guided underwater image enhancement network, uses the model-based principles as the guidelines to design a simple but effective model-guide sub-network to extract decent features, and simultaneously adopts a relatively small data-driven sub-network as the additive correction module to learn complementary features. Finally, the enhanced results are obtained by fusing the outputs of the two sub-networks. Experimental results show that, the proposed framework robustly achieves state-of-the-art performance over different underwater image datasets and substantially reduces the required network capacity.
Modeling the Yogyakarta International Airport (YIA) Area Flood Control System Using EPA SWMM 5.1

Yogyakarta International Airport (YIA) is a new airport that operates in the Special Region of Yogyakarta, located in Temon District, Kulon Progo Regency. The presence of the airport will undoubtedly bring various benefits, such as increasing economic activities in the area around the airport. However, the location has a problem, namely the risk of flooding. Flooding can affect activities around the airport, such as freight forwarding activities and access to or from the airport. Based on this problem, efforts are needed to prevent the flood that occurs does not have an impact on the activities of YIA airport and the surrounding area. In this case, the researcher used the EPA SWMM program in modeling the drainage system at the site under study. Modeling the point of occurrence of flooding will make it easier to normalize and add embankments to the channel. Modeling with EPA SWMM 5.1 requires input data such as rain distribution data, watershed characteristics, and the transverse appearance of the drainage channel. The results showed an overflow in the 15 drainage channels studied. The causes of overflow are high surface runoff and sedimentation based on channels and backwaters. Efforts to overcome by normalizing and adding embankments are sufficient to overcome flooding in several channels. Meanwhile, for channels that are still experiencing flooding, other countermeasures, such as retention ponds, are needed.
Peace Education in Schools through the Humanization of Conflict

Peace is nor peaceful or even attainable in its totality. It contains within itself conflict, it is a conflictual process always in formation: conflict is ambivalent, as destructive of relationships as it is the seed of peace, so it must not be eliminated or unleashed but governed. The teacher has the task of educating students to live together despite conflict and, more precisely, through conflict. Peace education is about humanizing conflict so that it unfolding brings benefit to the parties involved beyond the object of contention, enriching the experience with a common value-oriented plus of meaning. Strategies and tools: dialogical, narrative, mimetic and ethnographic method.
Feature extraction semilearning and augmented representation for image captioning in crowd scenes

Image captioning has been an interesting task since 2015. The topic lies in the gap between Computer Vision and Natural Language Processing research directions. The problem can be described as follows: Given the input as a three-channel RGB image, a language model is trained to generate the hypothesis caption that describes the images’ contexts. In this study, we focus on solving image captioning in images captured in a crowd scene, which is more complicated and challenging. In general, a semilearning feature extraction mechanism is proposed to obtain more valuable high-level feature maps of images. Moreover, an augmented approach in the Transformer Encoder is explored to enhance the representation ability. The obtained results are promising and outperform those of other state-of-the-art captioning models on the CrowdCaption dataset.
QR Code and Fingerprint Systems for University ExaminationsManagement

Several universities and other higher learning institutions throughout Tanzania use paper-based attendance systems and the old file system for recording student attendance during university examinations. The paper-based attendance system has several impediments, including chances of impersonation and the possibility of doing an examination without meeting requirements. Moreover, hard copy work is tedious and prone to vandalism or data loss due to paper misplacement or destruction. Several electronic general-purpose attendance systems and fewer attendance systems are engineered for university attendance management. However, university examination regulationsconflict with those systems. Henceforth, there is a gap in their applicability and adaptability. This study developed a QR code and fingerprint attendance prototype that resolves the shortcomings of existing electronic attendance systems. Fingerprints determined students’ identity during entry and exit sessions, while the QR code determined students’ examination answer booklet IDs during exit sessions. To assess the effectiveness of the attendance prototype, a sample of 120 students and 20 invigilators experimented with the prototype. The study findings show that the QR code and fingerprint systems are applicable and effective for managing university examination attendance in Tanzania. In addition, the study provides areas for future research
群ロボットでのParticle Swarm Optimizationへの制御バリア関数導入による探索性能の変容評価

We investigate the impact of introducing the collision avoidance constraint by the Control Barrier Function (CBF) on search performance of the Particle Swarm Optimization (PSO) algorithm. Swarm robot is superior to individual robots in terms of system flexibility, scalability, and fault tolerance. So, it is expected to effectively perform cooperative tasks, such as searching in a certain area. However, collision avoidance must be considered to ensure system safety and avoid robot failure. Therefore, it is necessary to achieve both search and collision avoidance when performing search on real robots. We discuss the chenge in search performance and search behavior by introducing collision avoidance of CBF.
機動力と作業能力両立のための空中離合体可能なクアッドロータユニットの実現

The article presents a new aerial robot unit that can perform both aerial assembly and disassembly. The robot is controlled as an under-actuated quadrotor in the unitary state and as a fully-actuated octocopter in the assembly state. The system includes novel docking mechanism, rotor configuration, and control system that enables the transition between two control models during assembly and disassembly motions. We also presents a motion strategy for aerial assembly and disassembly motion that includes a recovery action for hazardous states. The robot’s capabilities were tested through experiments, which demonstrated a success rate of aeiral assembly/disassembly is approximately 90%. Moreover, in the assembly state, the robot can utilize full-pose tracking and generate more than nine times the torque of a single unit. To the best of our knowledge, this is the first robot system that can perform both assembly and disassembly while seamlessly transitioning between fully-actuated and under-actuated models.
Estimation of upper body posture while riding a bicycle based on load measurement

Knowing one’s own movement and form in a sport, and getting close to the ideals, is essential for improvement in that sport. In cycling, pedaling motion and upper body posture are especially important for the rider to understand. Pedaling measurement methods are widely available. On the other hand, there is no easy way for riders to know their upper body posture. Therefore, we estimate upper body posture by using sensors that can be mounted on a bicycle. In this study, we measured the load on the handle and estimated the upper body posture based on the load. We created neural network models with the load as the input and the joint angle of the upper body as the output. The estimation accuracy was high when the model was based on personal data, but there was a problem with estimation accuracy when the model was based on other people’s data.
Estimation of Discomfort in Passengers on an Electronic Wheelchair by the surrounding three dimentional shape

When you get in automatic wheel chair, you may feel discomfort. This study assumes that the cause of the passenger’s feeling of anxiety is the surrounding environment, and aimed at generalizing passenger discomfort when the electric wheelchair is traveling autonomously．For this purpose, an experimental robot based on an electric wheelchair was used. By attaching 3D LiDAR as environmental observation devices to it, distance data of the robot’s surrounding environment is acquired. The acquired data is subjected to multiple regression analysis and regression analysis using a neural network to estimate the passenger’s sense of anxiety.
仮想環境での動的把持における振動グローブを用いた力分布の提示

In recent years, the use of virtual environments has attracted attention in various tasks such as education and development. Grasping movements are frequently performed in work, and changes in the force distribution of the hand appear due to the use of tools and the maintenance of a stable posture. In this study, we focus on a vibrotactile glove, which is small, lightweight and can present tactile sensations to various parts of the hand, and propose a vibration presentation referring to the force distribution in an actual dynamic grasping motion. For this purpose, we measured the force distribution during an actual swinging action of a stick and presented several vibration patterns when performing the same action in a virtual environment. We then conducted a questionnaire for each vibration pattern and investigated whether the vibration presentation considering the force distribution is suitable for the expression of dynamic grasping.
Whole-Body-Interactionを通した飛行ロボットとの共創アート

Drones have become famous and are used in various industrial fields. Recently, it comes into the spotlight that the study of interaction between human and flying robots (drones). There are various type of interfaces and interactions. However, despite importance of body, there are fewer studies on touch interaction with flying robots than those with ordinary robots. Thus, we developed touchable flying robot called “Soft Flying Robot”. This robot consists of a balloon and piezoelectric air pumps, which realize blade-free flight mechanism and safe touches. In addition, we design this robot more interactive, using touch sensors and LEDs. In this paper, we discuss about interaction design for Soft Flying Robot.
Implementation of Mechatronics Education Using Two-Wheel Drive Robot

In the future, the size of the domestic robotics market is expected to grow significantly, especially in the service and manufacturing industries, and the field of robot engineers is expected to expand. Our university is committed to fostering engineers and researchers in the fields of mechatronics and robotics who can respond to these needs. We have introduced mechatronics education in the form of competitions using 2-axis robots in the third-year seminar course, where students can learn electronic circuit design, control programming, and mechanical design through robot development. This paper describes the contents and issues of the practice course, which is in its fourth year of implementation.
空圧式ゴムバンドグリッパの改良

A rubber-band gripper that can grasp soft objects, such as tofu, without deforming them was improved. The improved gripper consists of four flexible actuators that shorten by expelling internal air. The gripper gently wraps around an object by controlling the vacuum pressure of each actuator. An attachment was also developed for the gripper to be mounted on a robot arm. The gripper, together with the attachment, can hold heavy objects and rotate doorknobs, which requires torque.
Drivable Area Extraction from Three-Dimensional Map Considering Step Climbing

This paper proposes a method of extracting areas where wheelchair users can drive from a three-dimensional map of the environment. The proposed method is characterized by its ability to detect steps that can be overcome by wheelchairs as the drivable areas in addition to flat ground. By an experiment using a drone and LiDAR, it is demonstrated that the proposed method can detect normal steps as drivable areas and convex-shaped steps, which are insurmountable by wheelchairs, as non-drivable areas. The proposed method can be easily applied to path planning for vehicles, mobile robots, and pedestrians besides wheelchairs.
Development of Paper Shape Estimation System for Origami Robot

In recent years, there has been a lot of research on deformable object manipulation. Our research group has been studying ”origami” as a manipulation of deformable objects by a multi-fingered robot hand. The shape of the paper was estimated by matching a physical model of the paper with observation point cloud. However, this method had a problem that the shape estimation became unstable when edges or a large portion of the point cloud was lost due to occlusion. In this study, we propose a method to supplement the lost point cloud with information observed by two micro cameras. In particular, a paper 3D point cloud is created from the images obtained by the micro cameras via a physical model and integrated into the main point cloud. Experimental results showed that the integration of the micro-camera point clouds with additional 3D information of the contours resulted in stable shape estimation.
移動ロボットによる対人サービスの受容性に関する意識調査

In cooperation with Ricoh Company, Ltd., we conducted an awareness survey on the introduction of tele-existence robots at Hitotsubashi University from both the users and accepting sides. Participants observed a robot driving and experienced VR and compared the acceptability of the robot before and after the experience.
VRシミュレータを用いた視線入力型電動車いす搭乗者の視線分析

Recently, there have been attempts to use eye gaze as an interface for electric wheelchairs. In this study, we develop a VR simulator for a gaze-input type electric wheelchair and measure gaze data to analyze gaze behavior during electric wheelchair operation.
Study on VO Execution Decision based on Variance of Image

Visual Odometry(VO) is a technique to estimate the position of a robot by using images. Compared to the wheel odometry, the VO is more accurate because it does not depend on the wheel slip. In a smooth surface environment such as sandy terrain, however, the VO fails to process because of the lack of feature points. In such an environment, it is better not to execute VO in order to reduce the processing load. Therefore, this paper proposes a method that decides whether VO is executable or not based on variance of image. The Random Forest-based classifier is trained using the images and archives high accuracy.
A Study on the Foot Sole Mechanism for Stable Walking in Rough Terrain Movement of Legged Mobile Robots

This paper describes the study on a legged mobile robot foot sole mechanism for use in unknown rough terrain movement. The mechanism has a structure consisting of three toes, and includes frictional locking and unlocking mechanisms by parallel links. The mechanism levels the bottom of the legged mobile robot’s foot by using the three toes when on unknown rough terrain. To stabilize the foot sole of the legged mobile robot on a level surface, the frictional locking and unlocking mechanisms connected to the three toes are used for the foot sole mechanism. Stable walking control of the legged mobile robot is simplified by the foot sole mechanism we developed.
Development of a telescopic manipulator using cylindrical spring

In this study, we developed a telescopic manipulator using a cylindrical spring. We installed iris hand at the tip of the manipulator. At the iris hand, we analyzed the range of three fingers grasping object and developed the iris hand with the optimal shape. The telescopic arm designed using speed control system and the hand operated by a single actuator were connected. In addition, by using a disturbance observer, equivalent disturbances due to weight can be suppressed, and it is possible to expand and contract stably even if there is a load at the tip of the cylindrical spring.
Development of a Mobile Robot “Phoenix-L” for Decommissioning Tasks

This paper reports an overview of a mobile robot “Phoenix-L” for decommissioning tasks and its evaluation tests. Phoenix-L consists of a vehicle mechanism “PHexa-L” and an arm mechanism “PArm-L”. PHexa-L is a six-wheeled vehicle that can control ground pressure by pneumatic control, and is easy to decontaminate and turn in a small space. The proposed differential wheel mechanism also enables to run over rough terrain. PArm-L has a coupled-drive structure in which all of the motor and sensors to control both the arm and the gripper are arranged in the base, and the entire structure is composed of only mechanical elements. Thus, it has high radiation resistance. Various tests using the prototype have confirmed the effectiveness of contact pressure control of the wheels, the ability to run over rough terrain, and the feasibility of light tasks.
Performance and Characterization of Disposable Robot Hand Made with Paper by Ribbon Origami Structure

In the food and other manufacturing industries, where the introduction of robots is expected to be promoted, hygienic and stable grasping technology is essential because of the need to handle goods with diverse characteristics. However, for companies, the high market cost of robot hands that meet the requirements is one of the factors restraining their introduction. In order to solve the problem of hygiene by using disposable robot hand, we devised an inexpensive disposable robot hand made of paper, verified the relationship between materials, structure, and grasping force, and studied the primary modeling of the force transmission mechanism of the robot hand in order to reduce the size and increase the grasping force.
腕の運動状態を用いたニューラルネットワークによる手首姿勢の運動予測

Myoelectric prostheses are useful for improving the quality of life of amputees. Although current myoelectric analysis research has focused on increasing the number of identifiable grasp shapes, few studies have focused on estimating wrist posture. Therefore, in this study, we focus on the relationship between arm and wrist posture, and estimate the wrist posture in grasping behavior from upper arm and forearm posture continuously. Specifically, LSTM, a neural network capable of dealing with time series information, was used to estimate the wrist posture 0.01s ahead, using the arm posture up to 1s ago as input. As a result, we successfully surprized estimate the average angular error to less than 3.3 degrees.
Comparison of Path Planning Methods with Constant Bending Angle Constraint for Soft Growing Robot

Path planning method is very important for mobile robots. However, existing path planning methods are not applied for our soft growing robot because its bending angles are constant value due to heat welding. Then, we developed some path planning methods whose path is composed with constant bending angle. In this paper, we compared the performance of these path planning methods. The result showed that the method whose nodes are rearranged to satisfy bending angle constraint after the simple path is obtained is not suitable in the environment that requires the path involving many bendings. Then, we convinced that the method that is based on RRT algorithm enables us to obtain the path faster than the method that based on the selections of the robot motion.
Teleoperation Method by Illusion of Human Intention and Time

Illusory control (IC) that is teleoperation method we proposed was based on the premise that the virtual environment is prepared in advance. Therefore, the mobile robot using IC can function only in known environment. This paper presents ”Instant illusory control” that no need to prepare the virtual environment in advance. The proposed robot system can instantly create a virtual environment from real images of the robot in motion using Instant NGP as one of methods in Neural Radiance Fields. Additionally, using 360-degree images, the environment around the robot can be comprehensively virtualized without demanding on the camera poses. Furthermore, using the depth estimation result of the images in advance for the optimization of the density of neural radiance fields, the reconstruction accuracy at unknown poses is ensured as well. Using this virtual environment instantly created, teleoperation by transition between real and virtual environments is expected to function in unknown environment. The experimental result shows that the proposed system can achieve a consistent back and forth between virtual and real spaces in mobile robot teleoperation.