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All Journal JAREE (Journal on Advanced Research in Electrical Engineering)
Mochammad Sahal
Institut Teknologi Sepuluh Nopember
Control & Systems Engineering Electrical & Electronics Engineering

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Obstacle Tracking on Unmanned Surface Vehicle Using Kalman Filter Rusdhianto Effendi Abdul Kadir; Mochammad Sahal; Yusuf Bilfaqih; Zulkifli Hidayat; Gaung Jagad
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 5, No 2 (2021): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v5i2.157

Abstract

Unmanned Surface Vehicles (USV) are self-driving vehicles that operate on the water surface. In order to be operated autonomously, USV has a guidance system designed for path planning to reach its destination. The ability to detect obstacles in its paths is one of the important factors to plan a new path in order to avoid obstacles and reach its destination optimally. This research designed an obstacle tracking system which integrates USV perception sensors such as camera and Light Detection and Ranging (LiDaR) to gain information of the obstacle’s relative position in the surrounding environment to the ship. To improve the relative position estimation of the obstacles to the ship, Kalman filter is applied to reduce the measurements noises. The results of the system design are simulated using MATLAB software so that results can be analyzed to see the performance of the system design. Results obtained using the Kalman filter show 12% noise reduction. Keywords: filter kalman, obstacle tracking, unmanned surface vehicle.
Dynamic Path Planning Of Unmanned Surface Vehicle Based On Genetic Algorithm With Sliding Curve Guidance System Rusdhianto Effendie Abdul Kadir; Mochammad Sahal; Nurlita Gamayanti; Fian Ilham Pratama
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 5, No 1 (2021): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v5i1.165

Abstract

Unmanned Surface Vehicle (USV) is an unmanned ship that is controlled through a remote control system (manual) or automatic control system (autopilot), move due to the thrust force from thruster machine and can turning due to the deflection angle of rudder. The USV path planning system becomes an important task so that the ship can make the global trajectory with the minimum travel distance according to the desired navigation while at the same able to avoid various obstacles from local dangerous situations that have the potential for collisions. To be able to do dynamic USV path planning, the Genetic Algorithm method with a sliding curve guidance system and PID MRAC controller is used. The use of this method gives smooth ship track performance with shortest distance in a 400x400 square meter map with static and dynamic obstacles. In a dynamic environment, the path replanning process that takes place in 0,98 seconds is able to find a new path that does not collide the obstacles. For the purposes of algorithm validation, the simulation is performed using MATLAB software with real ship parameters of 6 meters length USV.Keywords: dynamic and static obstacle, genetic algorithm, guidance system, path planning, PID MRAC, sliding curve, USV. 
Optimization of Vehicle Routing Problem with Tight Time Windows, Short travel time and Re-used Vehicles (VRPTSR) for Aircraft Refueling in Airport Using Ant Colony Optimization Algorithm Nurlita Gamayanti; Mochammad Sahal; Adi Wibisono
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 2, No 1 (2018): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25796216.v2.i1.40

Abstract

Scheduling in aircraft refueling has an important role in aviation. Scheduling of aircraft refueling is called Airport Ground Service Scheduling (AGSS) that can be formulated as Vehicle Routing Problem with Tight time windows, Short travel time and Re-used Vehicles (VRPTSR) This research is focusing in scheduling design for aircraft refueling with refueller truck in Juanda Airport, Surabaya, so minimum amount of truck will be used using Ant Colony optimization. The result shows that Ant Colony optimization could do scheduling in refueling well so minimum amount of truck will be used. Keywords: Scheduling, Vehicle Routing Problem with Tight time windows, Short travel time and Re-used Vehicles,  Ant Colony Optimization
Comparison of Gradient Estimation in Cooperative Multi-Agent Source Seeking Mochammad Sahal; Zulkifli Hidayat; Abdullah Alkaff
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 1, No 2 (2017): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25796216.v1.i2.21

Abstract

Agent-based source seeking problem is addressed in this paper. This problem is relevant in, e.g., in hazardous gas leak in a chemical disaster.  In the cooperative search, agents develop a formation to effectively search the source by communicating one to another via a communication topology. The source, or the search target, is represented by a scalar field y which might describe a temperature level, hazardous concentration of substances or vapor. Every agent has the information on its own position and the value of y at any instance. The agents are identical modeled as single and double integrator. Consensus filter is used to control the agent formation and comparison three types of gradient estimation are employed to search the source.  Experiments show that the proposed schemes give good performance to solve cooperative search for source seeking problem Keywords: cooperative source seeking, source seeking, formation control, gradient estimation
Smart Traffic Light Using YOLO Based Camera with Deep Reinforcement Learning Algorithm Mochammad Sahal; Zulkifli Hidayat; Yusuf Bilfaqih; Mohamad Abdul Hady; Yosua Marthin Hawila Tampubolon
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 1 (2023): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i1.335

Abstract

Congestion is a common problem that often occurs in big cities. Congestion causes a lot of losses, such as in terms of time, economy, to the psychology of road users. One of the causes of congestion is traffic lights that are not adaptive to the dynamics of traffic flow. This final project tries to solve this problem using a Reinforcement Learning approach combined with a SUMO (Simulation of Urban Mobility) traffic simulator. The data used is the real video data of the KD Cowek intersection, Surabaya. The video data is processed using the YOLO algorithm which will detect and count vehicles. The output of the video processing will be used in Reinforcement Learning. The result of Reinforcement Learning is that the total length of the traffic queue at 06.00 – 09.00 has an average of 106 vehicles.
Co-Authors Abdullah Alkaff Adi Wibisono Fian Ilham Pratama Gaung Jagad Hady, Mohamad Abdul Nurlita Gamayanti Rusdhianto Effendi Abdul Kadir Rusdhianto Effendie Abdul Kadir Yosua Marthin Hawila Tampubolon Yusuf Bilfaqih Zulkifli Hidayat Zulkifli Hidayat