다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Open Dynamics Engine を用いたスノーボードロボットシミュレータの開発

In this paper we provide a broad survey of developments in active vision in robotic applications over the last 15 years. With increasing demand for robotic automation, research in this area has received much attention. Among the many factors that can be attributed to a high-performance robotic system, the planned sensing or acquisition of perceptions on the operating environment is a crucial component. The aim of sensor planning is to determine the pose and settings of vision sensors for undertaking a vision-based task that usually requires obtaining multiple views of the object to be manipulated. Planning for robot vision is a complex problem for an active system due to its sensing uncertainty and environmental uncertainty. This paper describes such problems arising from many applications, e.g. object recognition and modeling, site reconstruction and inspection, surveillance, tracking and search, as well as robotic manipulation and assembly, localization and mapping, navigation and exploration. A bundle of solutions and methods have been proposed to solve these problems in the past. They are summarized in this review while enabling readers to easily refer solution methods for practical applications. Representative contributions, their evaluations, analyses, and future research trends are also addressed in an abstract level.

Active vision in robotic systems: A survey of recent developments

https://research.aalto.fi/files/11701996/1_s2.0_S174680941500021X_main.pdf

Current state of digital signal processing in myoelectric interfaces and related applications

This research investigates real time tilting measurement using Micro-Electro-Mechanical-system (MEMS) based inertial measurement unit (IMU). Accelerometers suffer from errors caused by external accelerations that sums to gravity and make accelerometers based tilting sensing unreliable and inaccurate. Gyroscopes can offset such drawbacks but have data drifting problems. This paper presents a study on complementary and Kalman filter for tilting measurement using MEMS based IMU. The complementary filter algorithm uses low-pass filter and high-pass filter to deal with the data from accelerometer and gyroscope while Kalman filter takes the tilting angle and gyroscope bias as system states, combining the angle derived from the accelerometer to estimate the tilting angle. The study carried out both static and dynamic experiments. The results showed that both Complementary and Kalman filter were less sensitive to variations and almost no signal coupling phenomenon and able to obtain smooth and accurate results.

MEMS based IMU for tilting measurement: Comparison of complementary and kalman filter based data fusion

We propose an electric wheelchair controlled by gaze direction and eye blinking. A camera is set up in front of a wheelchair user to capture image information. The sequential captured image is interpreted to obtain the gaze direction and eye blinking properties. The gaze direction is expressed by the horizontal angle of the gaze, and this is derived from the triangle formed by the centers of the eyes and the nose. The gaze direction and eye blinking are used to provide direction and timing commands, respectively. The direction command relates to the direction of movement of the electric wheelchair, and the timing command relates to the time when the wheelchair should move. The timing command with an eye blinking mechanism is designed to generate ready, backward movement, and stop commands for the electric wheelchair. Furthermore, to move at a certain velocity, the electric wheelchair also receives a velocity command as well as the direction and timing commands. The disturbance observer-based control system is used to control the direction and velocity. For safety purposes, an emergency stop is generated when the electric wheelchair user does not focus their gaze consistently in any direction for a specifi ed time. A number of simulations and experiments were conducted with the electric wheelchair in a laboratory environment.

Electric wheelchair control with gaze direction and eye blinking

The Kalman Filter is very useful in prediction and estimation. In this paper, the Kalman Filter is implemented for Inertial Measurement Unit (IMU) on the ATMega8535. The sensors used in this system are accelerometer MMA7260QT and gyroscope GS-12. The system chooses the arbitrary sampling time and then it is evaluated for possible using smaller value. As the Kalman Filter operation needs matrix calculation, the formula is converted into several ordinary equations. The parameter being investigated in this paper is measurement covariance matrix. This parameter influences the way the Kalman Filter responses to noise. Bigger value makes the Kalman Filter less sensitive to noise and the estimation is too smooth, thus it does not give real angle estimation. Using smaller value makes the Kalman Filter more sensitive to noise. This makes the estimated angle still suffers from noise and it is likely that the Kalman Filter is useless. This paper recommends 0.0001 to 0.001 for the measurement covariance noise parameter. This paper also recommended a pipeline configuration if the control algorithm needs more space in a sampling time.

Embedded Kalman Filter for Inertial Measurement Unit (IMU) on the ATMega8535

Abstrak Pada paper ini, kami mengusulkan sistem penghindaran halangan ganda (multiple moving obstacles) menggunakan stereo vision untuk service robot yang berada di lingkungan indoor. Kami menganggap model service robot ini digunakan untuk mengirimkan sebuah gelas ke pelanggan yang dikenal dari titik asal ke titik tujuan. Kontribusi dari penelitian ini ialah sebuah metode baru untuk penghindaran multiple moving obstacle dengan pendekatan Bayesian berbasis kamera stereo. Kami telah mengembangkan dan memperkenalkan 3 modul utama untuk mengenal wajah, mengidentifikasi multiple moving obstacles dan untuk manuver robot. Sekelompok orang yang berjalan di depan robot akan ditrack sebagai moving obstacles, serta kecepatan, arah dan jarak dari moving obstacles diestimasi menggunakan kamera stereo agar robot dapat bermanuver untuk menghindari tubrukan. Untuk mengatasi ketidakakuratan dari sensor vision, pendekatan Bayesian digunakan uintuk estimasi keberadaan dan arah moving obstacle. Hasil eksperimen dipaparkan dan kami evaluasi performa dari sistem service robot yang diberi nama Srikandi III. Berdasarkan eksperimen, metode yang kami usulkan berjalan dengan baik serta pendekatan Bayesian terbukti meningkatkan performa estimasi dari keberadaan dan arah halangan. Kata kunci: multiple moving obstacles, obstacle avoidance, service robot, stereo vision

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

In conditions that are dangerous for humans and their environment, the use of robots can be a solution to overcome these problems. Various sensors are used to determine the obstacle free path and the exact position of the robot. However, conventional sensors have limitations in terms of detection distance, spatial resolution, and processing complexity. In this study, an autonomous mobile robot has been developed equipped with Light Detection and Ranging (LiDAR) sensor to avoid obstacle. Braitenberg vehicle strategy is used to navigate the movements of the robot. Sensor data collection and control algorithm are implemented on a single computer board of Raspberry Pi 3. The experimental results show that this sensor can measure distance consistently which is not affected by the object's color and ambient light intensity. The mobile robot can avoid colored objects of different sizes. This autonomous mobile robot can also navigate inside a room without any impact on the wall or the obstacle.

Lidar-based Obstacle Avoidance for the Autonomous Mobile Robot

Hand Gesture Recognition sensor based on accelerometer and gyroscope is a sensor for capturing the positions of operator hand while controlling underwater remotely operated vehicle equipped with an arm. The proposed system has an advantage in its convenience by means of no training or exercise needed for operator before using it. The key issue here is how beginner operator could use easily the underwater remotely operated robot arm without any specific training. The conventional one uses a joystick for controlling the underwater system and it is inconvenience for beginner user as well as less precision. The proposed system consists of two main part: (1) ground station and (2) underwater remotely operated robot arm. This paper proposes the development of hand gesture recognition sensor used by operator at the ground station for controlling robot arm at the underwater robot. The proposed sensor uses accelerometers and gyroscopes installed in elbow, forearm, and wrist. These devices measure 3D position of each joints for constructing 3D position of hand. We design sensor's casing for its convenience of use by using CAD software. Each sensor is connected by Arduino Nano microcontroller having compact circuit and embedded it into sensor's casing. The sensors are connected to a microcontroller acting as master connected to microcontroller slave (sensor part). These sensors value are converted to 3D position by using forward kinematic. The forward kinematic values are sent to the underwater robot by using a wire utilizing Pulse Position Signal. Then, it converted again to servo's movement by using inverse kinematic. The result is operator able to control the underwater remotely robot arm by utilizing hand gesture directly. The last, operator could control the robot gripper based on flex sensor installed in operator's fingers. The accuracy of the sensor has been tested under laboratory condition, it has 98% of accuracy.

Djoko Purwanto

Papers

Electric wheelchair control with gaze direction and eye blinking

Embedded Kalman Filter for Inertial Measurement Unit (IMU) on the ATMega8535

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Lidar-based Obstacle Avoidance for the Autonomous Mobile Robot

Development of hand gesture recognition sensor based on accelerometer and gyroscope for controlling arm of underwater remotely operated robot