Real-time feature-based 3d map reconstruction for stereo visual guidance and control of mobile robots in indoor environments

2005 ◽  
Author(s):  
Wen-Chung Chang ◽  
Shu-An Lee
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Indoor Environments ◽  
Visual Guidance ◽  
Guidance And Control ◽  
Feature Based ◽  
And Control

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

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 Real-Time System Based on Feature Extraction for Vehicle Detection and Classification

2018 ◽  
Vol 19 (2) ◽  
pp. 93-102 ◽  
Author(s):  
Zakaria Moutakki ◽  
Imad Mohamed Ouloul ◽  
Karim Afdel ◽  
Abdellah Amghar
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Time Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Real Time System ◽  
Counting System ◽  
Feature Based ◽  
Traffic Video ◽  
And Control

Abstract Today, Road traffic video surveillance becomes the centre of several concerns. It presents an important way for analysis of road traffic in highways. Road traffic video surveillance can help to resolve many problems which can influence road safety. This paper presents a real-time management and control system which serve to analyze road traffic using a stationary camera. The proposed system can measure the quantity and characteristics of traffic in real time based on three modules, segmentation, classification and vehicle counting. Our contribution consists of developing a feature-based counting system for vehicle detection and recognition under the conditions which present a challenge in recent systems, such as occlusions, and illumination conditions. Our method can perform vehicle detection and classification by eliminating the influence of many factors on system efficiency. The obtained results show that the system proposed in this paper provides a counting rate higher than that of some existing methods.

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