Noorfadzli Abdul Razak

Single infra-red sensor technique for line-tracking autonomous mobile vehicle

Floor-based line-tracking technique is widely implemented for use in many autonomous mobile vehicle applications in the industries such as for transportation of goods within an enclosed warehouse or factories. It is also popular in competition robots. Many line-tracking systems utilize several kinds of discrete sensors such as the reflective infra-red LED, light dependent resistor (LDR), and multi-array inductance. Multiple of these discrete sensors are required to be arranged closed together in front of the vehicle and facing the floor to trace the profile of the line. A minimum of two sensors are required to ensure effectiveness of the line detection algorithm, especially to determine the vehicles position, either at left or at right with respect to line. This paper proposed a latest idea of using only one discrete sensor for mobile vehicle to detect a line having two colour shades on a white background surface. The results show that single sensor managed to allow the vehicle to maneuver as effectively on the line.

Model identification and real-time linear position control of servomotor

Plant model identification using experimental data is easy to be obtained with modern tools software such as Matlab and LabView. This powerful software provides reliable and approximate model structure. This paper presents model identification using Matlab System Identification Toolbox from open-loop input-output experimental data that obtained from linear position of a DC servo motor. The effectiveness of the proposed model was tested by a closed loop controller using pole-placement method. Simulation and real time control were conducted to show the reliability of the obtained model. The result shows acceptable performances in both simulation and real time studies.

Vision-based detection technique for effective line-tracking autonomus vehicle

An alternative means of implementing line detection technique to navigate autonomous mobile vehicles was investigated, specifically using vision sensor as the front end detection device. A vision sensor has the advantages of much higher spatial and optical resolutions as compared to the conventional discrete photo-reflective sensors used in most line-following mobile vehicles. It could offer better detection accuracy and reliability in varying lighting conditions. A selective video line technique was introduced and implemented which resulted in reduced number of video lines needs to be processed. Hence, avoiding the needs to use high-end processor to process and analyze the vast amount of information from the video images. There was enough space of information from each video line signal to be manipulated and could easily and flexibly calibrated with several lighting conditions. Abrupt changes in ambient lighting can be overcome without affecting the accuracy of the mobile vehicle navigation. A small inexpensive analog video camera, with standard video output signal had been chosen with a decent 8-bit microcontroller to process the video line signals and navigate the mobile vehicle.

A study of Kalman's filter in embedded controller for real-time quadrocopter roll and pitch measurement

Autonomous quadrocopter recently has shown a significant usages and potentials to be used widely in the commercial market. This caused the aircraft to become a well-liked subject among the researchers and research organizations. With good controllability and stability on its motions will make the usability of the quadrocopter to perform a task reliably. For this to happen, clean signals from accelerometer and gyroscope sensors appreciably play an essential role. However, the sensors signals are routinely encounter problems with noise and drift. Hence, a filter is required to correct this imperfectness. In this paper, a simplified algorithm for Kalmans filter appropriates to be used by a low-cost microcontroller is presented. The research mainly focuses on filtering noisy outputs from the accelerometer so that the output is necessarily clean to be used for real-time quadrocopter pitch and roll angles estimation. Experimental results on assessment of the algorithm by varying the process and measurement noises are provided. The results reveal with correct tuning on the noise parameters; the filter algorithm is satisfying to give stable angles values with fine accuracy.

Simultaneous localization and mapping based real-time inter-row tree tracking technique for unmanned aerial vehicle

This paper presents a review of previous work in the field of the unmanned autonomic vehicles in the agricultural field, particularly in the real-time inter-row tracking and localization techniques. A new method in row detection techniques based on simultaneous localization and mapping is proposed. The inter-row tracking technique differs from other available approaches done in terms of detection and navigation means. This technique is purposely for small-scaled unmanned aerial vehicle where substantial devices or equipments is unwelcome due to its enormous weight and size. Vision-based, laser-based and stereo vision-based techniques found to be an accurate row detection technique, however, proven to be impractical for on-board UAV detection and navigation implementation, as bulky computer as well as fast and robust processors is necessitated to perform all the massive computations and algorithmic tasks. In the way to maneuver the autonomic vehicles and robots to the admissible way points, the GPS receiver allows for precise in navigation and localization in the previous implementation. Unfortunately, it is impractical in applications where there are no GPS signals or receptions such as in the canopied environment like in the agriculture fields e.g. palm oil, rubber and papaya. Thus, the proposed new technique which applies an uncomplicated algorithmic sensory measurement at two visible landmarks, which are the trees, and uses them to predict the admissible way points for UAV navigation without carrying the burden cause by the substantial computers, monolithic computations and distortion of the GPS signals.

A Real-Time deviation detection and vector measurement technique for straight line quadrocopter navigation using accelerometer

In autonomous quadrocopter navigation, wind disturbances commonly pose a problem for the vehicle to navigate precisely on the planned path. The vehicle easily deviates off from the path and obviously affects the navigation accuracy. Trajectory correction is one possible solution proposed by few researchers to avert the problem. The approaches are proven to increase the efficiency for the vehicle to navigate on the path with tolerable accuracy error. Motivate by the solution, it is the intention for the research to advise a new trajectory correction algorithm known as a Real-Time Adaptive Trajectory Correction (RATC) algorithm. However, in this paper, a primary work for the algorithm definitely the deviation detection and vector measurement technique via an accelerometer is presented. The technique is designed based on trigonometric functions and vector synthesizing principle. A simplify Kalmans filter appropriately for low-cost onboard controller is employed to overcome the accelerometer drift and double integration error. The technique is evaluated in terms of measurement accuracy where an X-Y platform is utilized as the navigation path and control environment. The deviation vector is logged wirelessly in the Graphical User Interface (GUI) window which also programmed to exhibit visual deviation occurred on the quadrocopter. Three sets of experiment results with different wind disturbance acceleration are discussed. The results signified the technique has fine accuracy for short-duration measurement, especially navigation in a small-bounded area.

A real-time angle deviation detection and measurement technique for straight line quadrocopter navigation using accelorometer

Deviation from a planned path due to dynamic wind disturbances clearly will defect the quadrocopter navigation accuracy thus result to poor execution of a task. Few researchers proposed correction algorithms to be integrated in the autonomous quadrocopter system for the problem arises. However, the algorithms are not applicable to enable quadrocopter to navigate precisely on a planned trajectory around the small area with presences of dynamic disturbances such as wind. The research proposed a preliminary work for new real-time adaptive trajectory correction algorithm for autonomous quadrocopter, specifically the algorithm for angle deviation detection and measurement technique via an accelerometer. A ±3G analog accelerometer is utilized and being interfaced with a low-cost microcontroller for digitization process. For minimizing the fluctuation of accelerometer discrete signals, a simplified Kalmans filter algorithm appropriated for the controller is employed. The filtered signals are then used to sense the quadrocopter deviation from the planned path and compute the angle. A custom-made X-Y platform is used as the straight navigation path and represented as dynamic control environment. A GUI window is built in order to exhibit the visual deviation experienced by quadrocopter and recorded wirelessly the deviation angle from the controller so that evaluation on the accuracy performance can be analyzed. Three experiments with a different range of wind disturbance acceleration are executed where the results reveal that the technique is applicable to be used for short-duration detection and in a small-bounded area with fine accuracy.

Tree diameter measurement using single infrared sensor for non-stationary vehicle context in agriculture field

One of the important aspects in building an autonomous vehicle with the cognitive capability in agriculture field is the potentiality of it to recognize the trees or significant landmarks and map it for future navigation process. Therefore, it is crucial for a machine to detect the trees and keep tracking between them in order to perform the plantation activities autonomously. One of the challenges faced by this implementation is the need of a real-time tree detection technique which will not burden the processor as well as lightweight hardware that suits the needs of an autonomous aerial vehicle. Due to that, this paper presents a new and relatively simple tree diameter measurement technique using a high-performance and non-intrusive infrared sensor. The experiments are performed with a various coloured pole at a static velocity implementation to develop a promising technique that is useful and promising in this context.

Real-Time Optimal Trajectory Correction (ROTC) for Autonomous Omnidirectional Robot

This paper proposed a Real-Time Optimal Trajectory Correction (ROTC) algorithm designed to be applied for autonomous omnidirectional robot. It is programmed to work when a robot undergoes a deviation, an admissible trajectory correction path is generated for the robot rapidly returns to the route line. For the algorithm to do this, initially a deviation scheme is employed to sense deviation and formulates a vector consists of displacement and angle. Via the vector, an admissible correction path is originated utilizing Hermite cubic spline method fused with time and tangent transformation schemes. A Dead Reckoning (DR) technique is applied for robot to pursue the path. Several experiments are arranged to evaluate the reliability of robot navigation with and without the algorithm. It motion is mapped in Graphical User Interface (GUI) window using data from Laser Range Finder (LRF) sensors as attached to the robot controller. Using the map, the performances of the algorithm are evaluated in terms of distance travel and duration to return on the line. The results signify robot navigation with the algorithm required shorter distance and duration as compared to robot navigation without ROTC. Thus, it justifies the algorithm is feasible in the navigation system where it can assist robot effectively to move back to the route line after experiencing a deviation caused by a disturbance.

Single Wireless Electrocardiogram Monitoring and Acquisition System (SIWEMS)

Cardiovascular disease is the main cause of human casualty in the world as reported by World Health Organization (WHO). To facilitate in minimizing this cause, constant monitoring of the hearts rhythm appears to be essential in observing the condition of the heart by checking or recording the Electrocardiogram (ECG) signal. This paper presents a prototype design of Single Wireless Electrocardiogram Monitoring and Acquisition System (SIWEMS). The system is designed to implement Zigbee wireless technology for monitoring and storing an ECG signal remotely from a patient. The conceptual design of the system is discussed along with the circuits devised to generate a good-quality signal. Microcontrollers are employed to form a controller board for digitizing the signal and stored the signal in SD-card. Plus, the board is also interfaced with wireless module to transmit the signal to a Graphical User Interface (GUI) window. The GUI installed in laptop received the signal and concurrently displays it in real-time. Instead, the window does also provide data logger function. The proposed system is tested, and the results demonstrate it performs well to generate, displays and logs the ECG signal. Currently, this prototype is practically relevant to be employed for remote continuous dynamic monitoring and acquisition of ECG in healthcare.