Development in technology of information today provides various facilities to support human activity. One technology that facilitates human is the use of automated systems, the application of smart home system makes it easier for users to control household electronic devices. This study addresses one of the smart home solutions with automation systems. The system is built using ESP8266 and Raspberry Pi devices, by utilizing MQTT, REST and Laravel framework protocols. With Arduino, Python and PHP programming, household devices can be controlled both automatically and manually. Control system can be done by using web, chatbot, and physically. The communication used utilizes wireless network. With the designed system, the users can control the device, gain information and get warning. The information provided by the system is obtained from open data on the internet and from the sensor installed on the device.

This paper presents trajectory tracking on omni robots using odometry method. The odometry system aims to estimate the position relative to the initial position of the omni robot to estimate changes in position over time. The rotary encoder sensor is used to count the movement of the omni robot at the x and y coordinates in the odometry calculation process in this study. Furthermore, using the reverse kinematics on the omni robot, the rotational speed value of each DC motor in the omni robot wheel is obtained. In addition, to obtain the results of a good robot movement on the odometry system, PID control is applied to control the rotational speed of each DC motor on the omni robot wheel. With reverse kinematics and odometry systems, omni robot trajectory designs can be easily built. To test the odometry method performance in trajectory tracking process, there are three types of trajectory testing patterns, namely rectangles, equilateral triangles, and equilateral triangles. From the results of this test, the error value obtained is below 5%. Intisari-Makalah ini memaparkan trajectrory tracking pada robot omni dengan metode odometry. Sistem odometry bertujuan untuk memperkirakan posisi relatif terhadap posisi awal robot omni untuk memperkirakan perubahan posisi dari waktu ke waktu. Sensor rotary encoder digunakan untuk mencacah pergerakan robot omni pada koordinat x dan y pada proses perhitungan odometry. Selanjutnya, dengan menggunakan kinematika balik pada robot omni, nilai kecepatan putar masingmasing motor DC pada roda robot omni diperoleh. Selain itu, untuk memperoleh hasil pergerakan robot yang baik pada sistem odometry, kendali PID diterapkan untuk mengendalikan kecepatan putar masing-masing motor DC pada roda robot omni. Dengan kinematika balik dan sistem odometry, desain trajectory robot omni dapat dengan mudah dibangun. Untuk menguji kinerja metode odometry dalam melakukan proses trajectory tracking, terdapat tiga jenis pola pengujian trajectory, yaitu persegi panjang, segitiga sama sisi, dan segitiga sama kaki. Dari hasil pengujian ini, diperoleh nilai kesalahan di bawah 5%.

This paper presents a sensor-based stability walk for bipedal robots by using force sensitive resistor (FSR) sensor. To perform walk stability on uneven terrain conditions, FSR sensor is used as feedbacks to evaluate the stability of bipedal robot instead of the center of pressure (CoP). In this work, CoP that was generated from four FSR sensors placed on each foot-pad is used to evaluate the walking stability. The robot CoP position provided an indication of walk stability. The CoP position information was further evaluated with a fuzzy logic controller (FLC) to generate appropriate offset angles to be applied to meet a stable situation. Moreover, in this paper designed a FLC through CoP region's stability and stable compliance control are introduced. Finally, the performances of the proposed methods were verified with 18-degrees of freedom (DOF) kid-size bipedal robot.<br /><br />

Due to potential features of unmanned aerial vehicles for society, the development of bicopter has started to increase. This paper contributes to the development by presenting a performance evaluation of balancing bicopter control in roll attitude. It aims to determine the best controller structure for the balancing bicopter. The controller types evaluated are based on Ziegler-Nichols tuning method; they are proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers. Root locus plot of the closed-loop balancing bicopter system is used to decide the tuning approach. This work considers a difference in pulse-width-modulation (PWM) signal between the left and right rotors as the signal control and bicopter angle in roll movement as the output. Parameters tuned by the method are Kp, Ti, and Td which is based on the ideal PID structure. The performance test utilizes rising time, settling time, maximum overshoot, and steady-state error to determine the most preferred controller. The result shows that PI-controller has the best performance among the other candidates, especially in maximum overshoot and settling time. It reaches 8.34 seconds in settling time and 3.71% in maximum overshoot. Despite not being the best in rising time and resembling PID-controller performances in steady-state error criteria, PI-controller remains the most preferred structure considering the closeness of the response to the desired value.

This article describes the design and implementation of behavior-based robotic (BBR) algorithm on a wheeled mobile robot (WMR) Pioneer P3-DX in a maze exploration mission using V-REP simulator. This robot must trace and search for targets placed randomly on a labyrinth. After successfully meeting the objective, robot runs back to home position using the nearest path. Robot navigation system applies BBR algorithm to reach the target using behavior modules which work simultaneously to obtain the desired robot’s trajectory. The most fundamental behavior which is highly affordable to build on the robot system is a wall-following behavior. To make the robot could follow the wall in a safe, smooth and responsive condition, proportional-integral-derivative (PID) controller is applied. PID controller runs by utilizing the reading of sixteen proximity sensors carried on Pioneer P3-DX robot toward the expected wall distance while the robot is exploring the labyrinth. To ensure the designed system works properly, several tests were conducted, including BBR test and PID controller test. BBR test shows that the system can choose the shortest track when returning to home position. The PID controller test produces robot movement with maximum deviation and settling time for about 0.013 m and 30 seconds, respectively.