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

Enhancing Surgical Robot Precision With Advanced Datasets

The researchers introduce the ROSMA dataset and methodology in Applied Sciences, facilitating instrument detection and gesture segmentation in robotic surgical tasks. Through manual annotations and a neural network model combining YOLOv4 and LSTM, they achieve high accuracy and generalization capabilities, offering potential applications in surgical data science and beyond.

16 May 2024

How Are Robotics & Automation Redefining Environmental Sensing?

Researchers explore the transformative impact of automation and robotics on environmental sensing. They explored cutting-edge technologies such as environmental sensor networks (ESNs), unmanned aerial systems (UASs), robotics, and deep learning (DL), discussing their applications, challenges, and potential.

15 May 2024

Two-Finger Robotic Hand for Precise Object Manipulation

Researchers introduced a two-finger haptic robotic hand capable of manipulating objects with diverse stiffness levels and shapes. Utilizing force sensors and an impedance control algorithm, the hand demonstrated precise grasping and lifting abilities without causing damage or slippage.

14 May 2024

Neutrosophic Logic Revolutionizes Sign Language Recognition

Researchers introduced a novel approach to signer-independent sign language recognition (SLR) using Neutrosophic hidden Markov models (NHMM). By addressing the challenges of variability and uncertainty inherent in sign gestures, the proposed NHMM system achieved a remarkable gesture recognition rate of 98.5%, outperforming traditional methods.

13 May 2024

Improved Trajectory Tracking for Car-Like Mobile Robots

Researchers introduce a novel control scheme in Electronics journal to improve the trajectory tracking accuracy of car-like mobile robots (CLMRs) amidst modeling errors and external disturbances. By combining an extended state observer (ESO) and a backstepping controller, they effectively estimate and compensate for system uncertainties, promising enhanced performance for various CLMR applications.

9 May 2024

Exploring Embodied Intelligence in Soft Robotics

A recent review delves into the progress and future prospects of embodied intelligence in soft robotics, covering morphological computation, artificial evolution, perception, control, and decision-making. The study highlights synergies between soft robotics and embodied intelligence, presents applications across domains like exploration and medicine, and suggests directions for future research.

8 May 2024

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