0000000000173824
AUTHOR
Ajit Jha
showing 13 related works from this author
Camera-LiDAR Data Fusion for Autonomous Mooring Operation
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The use of camera and LiDAR sensors to sense the environment has gained increasing popularity in robotics. Individual sensors, such as cameras and LiDARs, fail to meet the growing challenges in complex autonomous systems. One such scenario is autonomous mooring, where the ship has to …
Classification of Targets Using Statistical Features from Range FFT of mmWave FMCW Radars
2021
Radars with mmWave frequency modulated continuous wave (FMCW) technology accurately estimate the range and velocity of targets in their field of view (FoV). The targeted angle of arrival (AoA) estimation can be improved by increasing receiving antennas or by using multiple-input multiple-output (MIMO). However, obtaining target features such as target type remains challenging. In this paper, we present a novel target classification method based on machine learning and features extracted from a range fast Fourier transform (FFT) profile by using mmWave FMCW radars operating in the frequency range of 77–81 GHz. The measurements are carried out in a variety of realistic situations, including p…
Autonomous Mooring towards Autonomous Maritime Navigation and Offshore Operations
2020
Bollard is a vital component of mooring system. It is the anchor point for mooring ropes to be fixed in order to secure the vessel or ship. An algorithm that translates the segmented mask of bollard output from masked R-CNN along with bounding box and associated class probability to its corresponding edge coordinate and finally to the single reference point for efficient detection and classification of bollard towards autonomous mooring is presented. At first stage, Mask R-CNN framework is trained with custom built bollard. The model obtained from the training is inferred with real data resulting in instance segment of bollard. The segmented mask obtained contains relatively large amount of…
A Self-Powered Long-range Wireless IoT Device based on LoRaWAN
2020
In this article, we propose a self-powered long-range wireless Internet-of-Things (IoT) device based on Long Range Wide Area Network (LoRaWAN) with various sensing capabilities. The nodes are designed based on ambient energy harvesting in such a way that these are self-sustainable throughout the components’ lifespan. Also, these nodes can be deployed on a large scale and are maintenance-free. In addition, these nodes can be deployed in remote places where the accessibility is limited, and maintenance is difficult. The wireless sensor nodes can be deployed both in indoor and outdoor environments with sufficient light levels for the solar panel, such as indoor lights in the indoor environment…
A Survey on Sensors for Autonomous Systems
2020
This paper presents a survey on state-of-the-art sensors for autonomous systems. The key performance parameters along with the operating principle of sensors used in autonomous systems are thoroughly explored. Practical aspects such as performance parameters, sensor output data format, sensor interfaces, size, power consumption, compatible hardware platforms, data analysis, and signal processing complexities are summarized. Such information serves as a practical guide for designing smart sensing systems for autonomous systems.
Optical method based detection and wavelets based processing of acoustic waves
2020
Acoustic waves (AW) has been used for the testing of static and dynamic structures. They contain the signature about the performance of rotary machines such as cyclic fatigue, friction, turbulence and cavitation. Thus has been extensively used in the condition monitoring and material characterization. In this paper, we present an algorithm based on wavelets to process the transient AW in time and frequency domain both simultaneously to extract its the temporal (e.g. time duration) and spectral properties (e.g. emission frequency). Further, optical method based on optical feedback (OF) is presented for detection of AW providing powerful non-contact, non-destructive diagnostic capabilities, w…
Current modulation induced stability in laser diode under high optical feedback strength
2021
The back-reflection of emitted laser beam (optical feedback, also know as selfmixing) from various external interfaces are sufficient to cause instability, and prohibiting its use in various fields such as communication, spectroscopy, imaging to name a few. So it is desirable to study the laser dynamics and the conditions causing it to be stable in spite of strong optical feedback. With the aid of mathematical formulation, simulation and backed by experimental evidences, it is demonstrated that the frequency deviation of the laser emission due to current (intensity) modulation alters the dynamic state and boundary conditions of the system such that even under large optical feedback strength…
A Velocity Estimation Technique for a Monocular Camera Using mmWave FMCW Radars
2021
Perception in terms of object detection, classification, and dynamic estimation (position and velocity) are fundamental functionalities that autonomous agents (unmanned ground vehicles, unmanned aerial vehicles, or robots) have to navigate safely and autonomously. To date, various sensors have been used individually or in combination to achieve this goal. In this paper, we present a novel method for leveraging millimeter wave radar’s (mmW radar’s) ability to accurately measure position and velocity in order to improve and optimize velocity estimation using a monocular camera (using optical flow) and machine learning techniques. The proposed method eliminates ambiguity in optical flow veloci…
Bollard Segmentation and Position Estimation From Lidar Point Cloud for Autonomous Mooring
2022
This article presents a computer-aided object detection and localization method from lidar 3-D point cloud data. This topic of interest is in the framework of autonomous mooring, where the ship is tied to the rigid structure on-shore (bollard) for autonomous maritime navigation. Using shape and features priors, unlike matching the whole object template to the experimental 3-D point cloud representation of the scene, two customized algorithms: 1) 3-D feature matching (3-DFM) and 2) mixed feature-correspondence matching (MFCM) are presented. The proposed algorithms discriminate and extract the 3-D points corresponding to the noncooperative bollard's surface from the background, thus capable o…
A Novel Angle Estimation for mmWave FMCW Radars Using Machine Learning
2021
In this article, we present a novel machine learning based angle estimation and field of view (FoV) enhancement techniques for mmWave FMCW radars operating in the frequency range of 77 - 81 GHz. Field of view is enhanced in both azimuth and elevation. The Elevation FoV enhancement is achieved by keeping the orientation of antenna elements in elevation. In this orientation, radar focuses the beam in vertical direction there by enhancing the elevation FoV. An Azimuth FoV enhancement is achieved by mechanically rotating the radar horizontally, which has antenna elements in the elevation. With the proposed angle estimation technique for such rotating radars, root mean square error (RMSE) of 2.5…
Robust Hand Gestures Recognition Using a Deep CNN and Thermal Images
2021
Medical systems and assistive technologies, human-computer interaction, human-robot interaction, industrial automation, virtual environment control, sign language translation, crisis and disaster management, entertainment and computer games, and so on all use RGB cameras for hand gesture recognition. However, their performance is limited especially in low-light conditions. In this paper, we propose a robust hand gesture recognition system based on high-resolution thermal imaging that is light-independent. A dataset of 14,400 thermal hand gestures is constructed, separated into two color tones. We also propose using a deep CNN to classify high-resolution hand gestures accurately. The propose…
Object Classification Technique for mmWave FMCW Radars using Range-FFT Features
2021
In this article, we present a novel target classification technique by mmWave frequency modulated continuous wave (FMCW) Radars using the Machine Learning on raw data features obtained from range fast Fourier transform (FFT) plot. FFT plots are extracted from the measured raw data obtained with a Radar operating in the frequency range of 77- 81 GHz. The features such as peak, width, area, standard deviation, and range on range FFT plot peaks are extracted and fed to a machine learning model. Two light weight classification models such as Logistic Regression, Naive Bayes are explored to assess the performance. Based on the results, we demonstrate and achieve an accuracy of 86.9% using Logist…
Deep Learning-Based Sign Language Digits Recognition From Thermal Images With Edge Computing System
2021
The sign language digits based on hand gestures have been utilized in various applications such as human-computer interaction, robotics, health and medical systems, health assistive technologies, automotive user interfaces, crisis management and disaster relief, entertainment, and contactless communication in smart devices. The color and depth cameras are commonly deployed for hand gesture recognition, but the robust classification of hand gestures under varying illumination is still a challenging task. This work presents the design and deployment of a complete end-to-end edge computing system that can accurately provide the classification of hand gestures captured from thermal images. A th…