Muhammad Osama

BTech(MechEng)

Mechanical Engineering with specialization in AI & Robotics

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence. Muhammad has worked on various research projects related to data analytics, machine learning, and deep learning for industries such as retail, medical, finance, agriculture, and Ed-Tech. He is enthusiastic and passionate about Artificial Intelligence-related research. Outside of work, he enjoys learning about new developments across all the fields related to science, technology, engineering, mathematics, and statistics.

Articles from Muhammad

Automating Abdominal Aortic Aneurysm Evaluation with Deep Learning

Researchers introduce a groundbreaking approach, leveraging deep learning and active learning techniques, to automate the measurement of abdominal aortic aneurysms (AAA) from computed tomography (CT) scans. This innovative workflow accurately segments AAA structures and provides automated measurements crucial for endovascular aneurysm repair (EVAR) planning, offering efficiency and precision in diagnosis and treatment.

7 May 2024

Cable-Driven Robotic Platform for Natural Head-Neck Movements

Researchers introduced a cable-driven robotic platform capable of facilitating six-degrees-of-freedom (6-DoF) natural head-neck movements without imposing rigid kinematic constraints. Through optimization and validation, the device demonstrated promising applications in rehabilitation, sports training, occupational therapy, and beyond, offering a versatile solution for enhancing human mobility and function.

6 May 2024

A Framework for Understanding Automation Disengagements

Researchers investigated factors contributing to automation disengagements in Tesla's Autopilot and Full Self-Driving (FSD) Beta systems. Through interviews with users, they identified categories such as human perception, operator states, and automation limitations, proposing a conceptual framework to predict and explain disengagement occurrences, crucial for system enhancement and user acceptance.

2 May 2024

Cable Loop Gripper for Robotic Automation

Researchers in the UK have introduced a cable loop gripper (CLG) designed to adeptly grasp objects of various shapes and sizes in chemistry labs. This innovative gripper, utilizing flexible cable loop technology, showcases promising potential for robotic automation in conducting chemistry experiments, offering adaptability, reliability, and efficiency in handling diverse laboratory supplies and equipment.

1 May 2024

Next-Level Robotics: Enhancing Accuracy with Advanced Multisensory Interfaces

Researchers introduced an advanced multisensory interface in Actuators journal, enhancing robot-assisted pouring tasks with detailed sensory feedback while managing high visual demands. Their optimization method identified the most effective combination of feedback modalities, maximizing perception while minimizing cognitive load.

30 Apr 2024

Advancing Agriculture Drone Control with Hybrid Fuzzy PID Controllers

Researchers introduced hybrid fuzzy PID controllers for quadcopter drones in agriculture, combining the adaptability of fuzzy logic with the precision of classical PID control.

29 Apr 2024

SMR-O: Advancing Miniature Quadrupedal Piezoelectric Robots

Researchers developed SMR-O, a miniature quadrupedal piezoelectric robot, leveraging a novel spatial parallel mechanism and innovative piezoelectric actuator manufacturing. With peak speeds of 48.66 cm/s and a payload capacity of 5.5 g, SMR-O demonstrates rapid and agile locomotion, promising applications in search and rescue, exploration, medical diagnostics, and fault detection.

25 Apr 2024

Enhancing Industrial Robot Performance Through Time-Lag Filtering

Researchers from China proposed a novel method for reducing vibrations in industrial robots through time-lag filtering based on trapezoidal trajectory interpolation. This technique targets enhancing motion accuracy and stability by reducing harmonic components' amplitudes within specific frequency bands.

24 Apr 2024

Intelligent Indoor Robot for Object Detection, Mapping, and Navigation

This paper introduces an intelligent indoor service robot designed for tasks like object recognition, path planning, and obstacle avoidance. Leveraging ROS framework and deep learning techniques, the robot employs YOLOv3 for object detection and compares different SLAM algorithms for mapping and navigation.

23 Apr 2024

Advancing Robotic Technology in Coal Mining

Researchers proposed an advanced framework for robotic technology systems in coal mining operations to enhance safety, efficiency, and intelligence. They conducted a comprehensive review of coal mining robots, highlighting achievements, innovations, and challenges.

22 Apr 2024