Arman Asgharpoor Golroudbari

University of Tehran | UT · Department of Aerospace Engineering

This paper presents a novel end-to-end deep learning framework for real-time inertial attitude estimation using 6DoF IMU measurements. Inertial Measurement Units are widely used in various applications, including engineering and medical sciences. However, traditional filters used for attitude estimation suffer from poor generalization over differen...

This review article presents recent advancements in deep learning methodologies and applications for autonomous navigation. It analyzes state-of-the-art deep learning frameworks used in tasks like signal processing, attitude estimation, obstacle detection, scene perception, and path planning. The implementation and testing methodologies of these ap...

This review article presents recent advancements in deep learning method-ologies and applications for autonomous navigation. It analyzes state-of-the-art deep learning frameworks used in tasks like signal processing, attitude estimation, obstacle detection, scene perception, and path planning. The implementation and testing methodologies of these a...

This review article presents recent advancements in deep learning methodologies and applications for autonomous nav- igation. It analyzes state-of-the-art deep learning frameworks used in tasks like signal processing, attitude estimation, ob- stacle detection, scene perception, and path planning. The implementation and testing methodologies of thes...

This paper presents a novel end-to-end deep learning framework for real-time inertial attitude estimation using 6DoF IMU measurements. Inertial Measurement Units are widely used in various applications, including engineering and medical sciences. However, traditional filters used for attitude estimation suffer from poor generalization over differen...

This thesis proposes a novel end-to-end deep learning framework for real-time inertial attitude estimation using 6DoF IMU measurements, which integrates accelerometer and gyroscope readings as inputs. The framework is designed to be generalizable to various motion patterns, sampling rates, and environmental disturbances, and consists of Convolution...

This review paper presents a comprehensive overview of end-to-end deep learning frameworks used in the context of autonomous navigation, including obstacle detection, scene perception, path planning, and control. The paper aims to bridge the gap between autonomous navigation and deep learning by analyzing recent research studies and evaluating the...

Inertial Measurement Units (IMU) are commonly used in inertial attitude estimation from engineering to medical sciences. There may be disturbances and high dynamics in the environment of these applications. Also, their motion characteristics and patterns also may differ. Many conventional filters have been proposed to tackle the inertial attitude e...

This thesis proposes a novel end-to-end deep learning framework for real-time inertial attitude estimation using 6DoF IMU measurements, which integrates accelerometer and gyroscope readings as inputs. The framework is designed to be generalizable to various motion patterns, sampling rates, and environmental disturbances, and consists of Convolution...

A Fuzzy Approach for NEOs risk assessment.

Fuzzy Logic: History of T-norms

3rd round | USERN MTalk Appreciated Presentation

Determine the position, velocity, and orbit (in 3D) of satellite with given the initial vector (r0 &v0), using MATLAB

Kalman Filter Based Estimation State estimation algorithm

Pseudo Five DoF Equations of Motion

Position and Velocity as a Function of Time