scholarly journals Real-Time Fusion of Visual Images and Laser Data Images for Safe Navigation in Outdoor Environments

10.5772/16690 ◽  
2011 ◽  
Author(s):  
Maria C. ◽  
David Martin ◽  
D. Miguel ◽  
Domingo Guine
Keyword(s):  
Real Time ◽  
Visual Images ◽  
Safe Navigation ◽  
Laser Data ◽  
Outdoor Environments

scholarly journals Monitoring Real-time Personal Locomotion Behaviors over Smart Indoor-outdoor Environments via Body-Worn Sensors

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Munkhjargal Gochoo ◽  
Sheikh Badar Ud Din Tahir ◽  
Ahmad Jalal ◽  
Kibum Kim
Keyword(s):  
Real Time ◽  
Outdoor Environments

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

A method for real-time safe navigation in noisy environments

2013 ◽  
Author(s):  
Seyed Ali Salehi Neyshabouri ◽  
Mohammad Reza Niknezhad ◽  
Ehsan Kamali ◽  
Seyed Sadegh Mohseni Salehi Monfared
Keyword(s):  
Real Time ◽  
Noisy Environments ◽  
Safe Navigation

scholarly journals Formaldehyde and Glyoxal Measurement Deploying a Selected Ion Flow Tube Mass Spectrometer (SIFT-MS)

2021 ◽  
Author(s):  
Antonia Zogka ◽  
Manolis N. Romanias ◽  
Frederic Thevenet
Keyword(s):  
Proton Transfer ◽  
Real Time ◽  
Mass Spectrometer ◽  
Sharp Decrease ◽  
Ionization Mass ◽  
Flow Tube ◽  
Experimental Conditions ◽  
Ion Flow ◽  
Outdoor Environments ◽  
Selected Ion Flow Tube

Abstract. Formaldehyde (FM) and glyoxal (GL) are important atmospheric species of indoor and outdoor environments. They are either directly emitted in the atmosphere or they are formed through the oxidation of organic compounds by indoor and/or outdoor atmospheric oxidants. Despite their importance, the real-time monitoring of these compounds with soft ionization mass spectrometric techniques, e.g. proton transfer mass spectrometry (PTR-MS), remains problematic and is accompanied by low sensitivity. In this study, we evaluate the performance of a multi-ion selected ion flow tube mass spectrometer (SIFT-MS) to monitor in real-time atmospherically relevant concentrations of FM and GL under controlled experimental conditions. The SIFT-MS used is operated under standard conditions (SC), as proposed by the supplier, and customized conditions (CC), to achieve higher sensitivity. In the case of FM, SIFT-MS sensitivity is marginally impacted by RH, and the detection limits achieved are below 200 ppt. Contrariwise, in the case of GL, a sharp decrease of instrument sensitivity is observed with increasing RH when the H3O+ ion is used. Nevertheless, the detection of GL using NO+ precursor ion is moderately impacted by moisture with an actual positive sensitivity response. Therefore, we recommend the use of NO+ precursor for reliable detection and quantitation of GL. This work evidences that SIFT-MS can be considered as an efficient tool to monitor the concentration of FM and GL using SIFT-MS in laboratory experiments and potentially in indoor or outdoor environments. Furthermore, SIFT-MS technology still allows great possibilities for sensitivity improvement and high potential for monitoring low proton transfer affinity compounds.

scholarly journals Autonomous and Safe Navigation of Mobile Robots in Vineyard with Smooth Collision Avoidance

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 954
Author(s):  
Abhijeet Ravankar ◽  
Ankit A. Ravankar ◽  
Arpit Rawankar ◽  
Yohei Hoshino
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Autonomous Robots ◽  
Robot Navigation ◽  
Indoor Environments ◽  
Safe Distance ◽  
Field Robots ◽  
Safe Navigation

In recent years, autonomous robots have extensively been used to automate several vineyard tasks. Autonomous navigation is an indispensable component of such field robots. Autonomous and safe navigation has been well studied in indoor environments and many algorithms have been proposed. However, unlike structured indoor environments, vineyards pose special challenges for robot navigation. Particularly, safe robot navigation is crucial to avoid damaging the grapes. In this regard, we propose an algorithm that enables autonomous and safe robot navigation in vineyards. The proposed algorithm relies on data from a Lidar sensor and does not require a GPS. In addition, the proposed algorithm can avoid dynamic obstacles in the vineyard while smoothing the robot’s trajectories. The curvature of the trajectories can be controlled, keeping a safe distance from both the crop and the dynamic obstacles. We have tested the algorithm in both a simulation and with robots in an actual vineyard. The results show that the robot can safely navigate the lanes of the vineyard and smoothly avoid dynamic obstacles such as moving people without abruptly stopping or executing sharp turns. The algorithm performs in real-time and can easily be integrated into robots deployed in vineyards.

scholarly journals Uncertainty-Aware Visual Perception System for Outdoor Navigation of the Visually Challenged

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2385 ◽  
Author(s):  
George Dimas ◽  
Dimitris E. Diamantis ◽  
Panagiotis Kalozoumis ◽  
Dimitris K. Iakovidis
Keyword(s):  
Visual Perception ◽  
Obstacle Detection ◽  
Generative Adversarial Networks ◽  
Safe Navigation ◽  
Perception System ◽  
Outdoor Environments ◽  
Visual Aid ◽  
Fuzzy Logic Approach ◽  
Visually Challenged ◽  
Outdoor Navigation

Every day, visually challenged people (VCP) face mobility restrictions and accessibility limitations. A short walk to a nearby destination, which for other individuals is taken for granted, becomes a challenge. To tackle this problem, we propose a novel visual perception system for outdoor navigation that can be evolved into an everyday visual aid for VCP. The proposed methodology is integrated in a wearable visual perception system (VPS). The proposed approach efficiently incorporates deep learning, object recognition models, along with an obstacle detection methodology based on human eye fixation prediction using Generative Adversarial Networks. An uncertainty-aware modeling of the obstacle risk assessment and spatial localization has been employed, following a fuzzy logic approach, for robust obstacle detection. The above combination can translate the position and the type of detected obstacles into descriptive linguistic expressions, allowing the users to easily understand their location in the environment and avoid them. The performance and capabilities of the proposed method are investigated in the context of safe navigation of VCP in outdoor environments of cultural interest through obstacle recognition and detection. Additionally, a comparison between the proposed system and relevant state-of-the-art systems for the safe navigation of VCP, focused on design and user-requirements satisfaction, is performed.

Real-time sound propagation and noise modeling in outdoor environments using Equivalent Source Formulation

2012 ◽  
Vol 132 (3) ◽  
pp. 1890-1890 ◽  
Author(s):  
Ravish Mehra ◽  
Dinesh Manocha ◽  
Lakulish Antani ◽  
Nikunj Raghuvanshi
Keyword(s):  
Real Time ◽  
Sound Propagation ◽  
Equivalent Source ◽  
Noise Modeling ◽  
Outdoor Environments
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