Advanced Mechanical and Mechatronic Systems

A Robot for Collecting Objects Based on the Convolutional Neural Network Method and Inertial Measurement Unit Sensor

2025-07-22T01:55:32+00:00

This study presents the development of an autonomous mobile robot for real-time object detection and collection by integrating a Convolutional Neural Network (CNN) with an Inertial Measurement Unit (IMU). The primary objective is to design, implement, and evaluate a sensor-fusion-based robotic system capable of detecting objects through image recognition, estimating orientation and motion via inertial sensing, and performing automated retrieval tasks in structured and semi-structured environments. The CNN is trained to recognize and localize objects using real-time video input, while the IMU provides data on the robot’s pose and dynamics. Through sensor fusion algorithms, the system achieves improved situational awareness, stability, and navigation accuracy. A closed-loop control framework translates sensory data into motion commands for the robot’s differential drive and gripper, enabling reliable object approach, grasping, and transport. Experimental results demonstrate high classification accuracy and a grasping success rate exceeding 85% in indoor tests. The proposed approach shows strong potential for applications in logistics, smart manufacturing, and service robotics, where repetitive object-handling tasks can be automated with reliability.

Integration of Vehicle Tracking, Control and Maintenance

2025-08-10T12:39:31+00:00

This research developed a vehicle tracking and control system aimed at improving fleet management efficiency in Batam. The problem addressed was the lack of an integrated solution that combined location monitoring, remote control, and service management for vehicles. The system integrated the ESP8266 microcontroller as the control unit, a Ublox Neo 6M GPS module for location tracking, a relay for engine control, and a SIM/GSM module for communication via HTTP. Data were stored in a PostgreSQL server and visualized using a web application developed with Node.js, Next.js, and Leaflet.js. The research objectives were to design, implement, and test a system capable of real-time vehicle monitoring, speed detection, and remote engine shutdown, accessible through a web browser on both computers and mobile devices. Testing was carried out using a motorcycle in the Batam Center area, showing that GPS readings, relay control, and data transmission were successfully executed. The highest longitude error observed was 0.000022, which remained within acceptable tolerance. The findings demonstrated that the system provided accurate and reliable vehicle tracking while offering practical solutions for fleet control. In conclusion, the developed system supported efficient vehicle management and could be further enhanced for broader fleet applications in urban areas.

Numerical Study: Crashworthiness of Hydrogen Powered Vehicle in a Collision

2025-08-04T12:07:06+00:00

This numerical research focuses on the crashworthiness of a hydrogen powered vehicle in a collision including the safety of the hydrogen storage system. The model of the vehicle and the hydrogen storage system were developed in Ansys Space Claim. In another Ansys tool, Mechanical, the simulations for three crash scenarios were conducted. The simulations involved the modelled vehicle with the hydrogen system impacting a rigid wall in frontal, rear and side scenarios to assess the amount of deformation, stress distribution and the internal/total energy absorbed by the tanks. The results from the simulations showed that there was significant deformation and stress experienced by the hydrogen storage system. maximum stress values from the frontal impact were 4630.2 MPa which is way over values of typical failure points of Type IV tanks. From the side impact, it was noted too that the tanks had higher internal energy absorbed when compared to the other 2 scenarios. The recorded value of this amount of energy was 255.32 J and show there is a high risk of the tank rupturing or leaking. The data was analysed with other literature values confirming the found data from the simulations conducted. These findings demonstrate that even though the current configuration of the hydrogen system has less risk of failure from minor impacts, they are still in a state of vulnerability under severe crashes. Furthermore, the findings highlight the continued need of research on improving the configuration of storage systems, better protection systems and inclusion of many more parameters.

Gait Generation Using a Fourier Series for a Quadruped Robot with 2-DoF Legs

2025-10-11T01:43:07+00:00

This study proposed the development of a quadruped cat robot designed to achieve straight-line walking motion inspired by a cat’s gait. The objective was to enhance cat-like robotic mobility by addressing challenges in gait planning and joint coordination. The robot was constructed with 2 degrees of freedom (DoF) for each leg, using lightweight materials such as acrylic, plywood, and aluminum to balance strength and maneuverability. Geometric kinematic equations were applied to model the end-effector positions, and a Fourier series was employed to generate a smooth, periodic trajectory for the foot’s end-effector, minimizing jerky movements. The Fourier series fitting achieved high accuracy (R² ≈ 0.99) for the joint angles. The resulting prototype, controlled by an Arduino microcontroller, successfully demonstrated a stable and periodic gait cycle generated through the Fourier series approach, confirming the viability of this kinematic method for straight-line motion.

Customized Prosthetic Feet via Topology Optimization and 3D Printing: A Critical Review

2025-07-30T13:42:22+00:00

This critical review examines the transformative impact of integrating topology optimization and additive manufacturing (AM) on the design and production of transtibial prosthetic feet. By systematically surveying peer-reviewed studies published between 2010 and 2024, this work highlights how computational algorithms—such as SIMP, level-set, and evolutionary methods—can achieve mass reductions of 50–70% while maintaining safety factors above 1.5. Concurrently, AM technologies including FDM, SLS, and SLA faithfully reproduce complex, patient-specific geometries with deviations under 5% from finite element analysis (FEA) predictions. Material innovations span thermoplastics (PLA, nylon 66), advanced composites (CFRP, titanium lattices), and emerging smart materials (shape-memory polymers, piezoelectric composites), collectively enhancing energy return by up to 30% and fatigue life by more than 10⁵ cycles. Comprehensive validation—encompassing ISO 10328 static testing, dynamic fatigue trials, gait simulations, and wearer trials—confirms both mechanical integrity and user comfort, aided by integrated sensor systems for real-time performance monitoring. Regulatory and clinical pathways, including ISO 13485, FDA 510(k), MDR, and ISO 14155 guidelines, are discussed to facilitate translation into practice. Future research should focus on multicenter clinical trials, open-access design repositories, adaptive materials, and machine learning–driven predictive maintenance to propel patient-centered innovation in prosthetic care.