Jerk-Bounded Trajectory Generation Method using Digital Convolution

This paper proposes a jerk-bounded trajectory generation method using a digital convolution. The suggested jerk-bounded trajectory is able to reduce unexpected damages for a robot motion control system and to improve a tracking accuracy/speed of the control system. Also, it can be implemented in real-time because it requires low computational loads. The effectiveness of the suggested method is shown through numerical simulations for a point-to-point (PTP) motion generation application

Development Of Pipeline Corrosion Inspection System Using Machine Vision

These days, utilization of camera as an inspection tool has been expanded. The flexible function of camera is adequate to obtain different kind of information. In Cawley (2001) review on NDT that was presented in 2001, Radiography, Ultrasonic, Eddy Current, Magnetic Particle, and Penetrant Testing were the top five techniques dominating the NDT market yet Visual Inspection is the most widely applied. Even though the popularity of visual inspection is higher compared to other NDT method, but due to the reliability issues it is often used together with other methods. This research work is focusing on developing a robust corrosion inspection system based on vision sensor that is able to accurately detect and classify corrosion based on the appearance features. By installing at an early stage, inspection system would be able to gather data and at the same time identify and analyse the collected data. Through the results, the analysed data is able to classify the corrosion type based on appearance. From the research work, the method of using image enhancement filters to improve accuracy of vision corrosion inspection system is identified. The detection of each macroscopic surface corrosion types; galvanic; crevice; erosion; pitting and exfoliation using vision inspection able to achieve 79% accuracy using the simulated dataset. The new method of corrosion inspection operation which able to generate prevention plan has qualified the Vision Corrosion Inspection System to be used during preliminary inspection. It is expected that the Vision Corrosion Inspection System can improve vision inspection as the pioneer in NDT method for corrosion inspection. In addition, framework of the developed Vision Corrosion Inspection system is applicable for other applications of vision inspection whereby it can be applied for other inspection process or extending its application to other problems

Automatic Floor Cleaning Robot Using Arduino and Ultrasonic Sensor

The entire floor cleaning robot is divided into several parts, namely consisting of an Ultrasonic Sensor, Motor Shield L298, Arduino Uno microcontroller, Servo, and Dc Motor. This tool works when the Arduino Uno microcontroller processes the ultrasonic sensor as a distance detector and a DC motor as a robot driver, then the DC motor is driven by the Motor Shield L298. When an ultrasonic sensor detects a barrier in front of it, the robot will automatically look for a direction that is not a barrier to the floor cleaning robot. The distance value on the sensor has been determined, that is, when the distance read by the ultrasonic sensor is below 15 cm. The results of testing the value of the ultrasonic sensor distance found different conditions that occur. In a distance of 15 cm, the condition of the prototype cleaning robot for the road floor cleaning is obtained, while the distance 15 cm, the condition for the prototype of the street floor cleaning robot has stopped

Q Learning Behavior on Autonomous Navigation of Physical Robot

Behavior based architecture gives robot fast and reliable action. If there are many behaviors in robot, behavior coordination is needed. Subsumption architecture is behavior coordination method that give quick and robust response. Learning mechanism improve robot’s performance in handling uncertainty. Q learning is popular reinforcement learning method that has been used in robot learning because it is simple, convergent and off policy. In this paper, Q learning will be used as learning mechanism for obstacle avoidance behavior in autonomous robot navigation. Learning rate of Q learning affect robot’s performance in learning phase. As the result, Q learning algorithm is successfully implemented in a physical robot with its imperfect environment

The intelligent room for elderly care

Daily life assistance for elderly is one of the most promising and interesting scenarios for advanced technologies in the present and near future. Improving the quality of life of elderly is also some of the first priorities in modern countries and societies where the percentage of elder people is rapidly increasing due mainly to great improvements in medicine during the last decades. In this paper, we present an overview of our informationally structured room that supports daily life activities of elderly. Our environment contains different distributed sensors including a floor sensing system and several intelligent cabinets. Sensor information is sent to a centralized management system which processes the data and makes it available to a service robot which assists the people in the room. One important restriction in our intelligent environment is to maintain a small number of sensors to avoid interfering with the daily activities of people and to reduce as much as possible the invasion of their privacy. In addition we discuss some experiments using our real environment and robot