Obstacle Warning System Research Articles

Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

To be able to do their daily activities, a visually impaired person needs a guidance device to help him/her walk including to avoid obstacles on their way to the destination. The quick and clear instruction is given to the user is the most challenging problem to be solved. The visually impaired person should have simple guidance about the obstruction in front of him/her. Most guidance devices use simple sounds to give the warning without information about which direction the user should go. In this paper, an obstacle warning system based on image processing methods was developed. A guidance device for visually impaired persons using a single-board computer based on an image-processing algorithm has been designed. The main sensor of the guidance device is a NoIR camera. The distance measurement approximation model was developed with errors up to 4.3%. The test found that the proposed system can detect obstruction in the form of a person, the device also detects the stairs. The best detection obtains when the object position is less than 300 cm in front of the user. The stair detection was carried out by using the Hough line transform method. The output of the system is the sound of direction that can be heard through the headset.

SIGNAL PROCESSING IN A ROBOTIC VEHICLE OBSTACLE WARNING RADIO SYSTEM IN THE SUBTERAHERTZ FREQUENCY RANGE

The article describes the features of the implementation of radars with the synthesis of the anterolateral viewing aperture in the subterahertz frequency range, designed to implement an obstacle warning system for a robotic vehicle. It is shown that vibrations with standard deviation systems of about 1 mm representa significant problem for the implementation of SAR modes in the W range. In order to overcome this problem, it is proposed to use Bayesian algorithms for the formation of radar images in conditions of a priori uncertainty.

Prototype of Bridge Navigational Watch Alarm System Equipped Obstacle Warning System Based on Image Processing and Real-Time Tracking

Ships are sea transportation that is often used in Indonesia. However, who would have thought that the transportation would become a case because of the frequent occurrence of accidents. This has been proven from data from the KNKT (National Transportation Safety Committee) which noted that from 2012 to 2017 there had been an increase in accidents in the waters. In fact, according to the National Search and Rescue Agency (Basarnas) in 2020 there have been 878 incidents with victims reaching 4658 people. In this final project, the author makes a prototype of BNWAS (Bridge Navigational Watch Alarm System) equipped with obstacle warning using image processing with the otsu method strengthened by thresholding-based segmentation with inverse technique (TsTN), distance detection using the triangle similarity method, real-time tracking with GPS (Global Positioning System) and the entire system can be observed on the Android application. The Final Project performs several analyzes including performance analysis by calculating the accuracy of the BNWAS alarm system, image detection accuracy, distance detection accuracy, GPS accuracy, overall system testing accuracy and packet loss. The accuracy of each system is very good because the error is below 2%, while for overall system testing has a very good performance with a delay of 179.8 ms and 0% packet loss.

Obstacle detection and warning system for visually impaired people based on electrode matrix and mobile Kinect

Obstacle detection and warning can improve the mobility as well as the safety of visually impaired people specially in unfamiliar environments. For this, firstly, obstacles are detected and localized and then the information of the obstacles will be sent to the visually impaired people by using different modalities such as voice, tactile, vibration. In this paper, we present an assistive system for visually impaired people based on the matrix of electrode and a mobile Kinect. This system consists of two main components: environment information acquisition and analysis and information representation. The first component aims at capturing the environment by using a mobile Kinect and analyzing it in order to detect the predefined obstacles for visually impaired people, while the second component tries to represent obstacle’s information under the form of electrode matrix.

LIDAR obstacle warning and avoidance system for unmanned aerial vehicle sense-and-avoid

The demand for reliable obstacle warning and avoidance capabilities to ensure safe low-level flight operations has led to the development of various practical systems suitable for fixed and rotary wing aircraft. State-of-the-art Light Detection and Ranging (LIDAR) technology employing eye-safe laser sources, advanced electro-optics and mechanical beam-steering components delivers the highest angular resolution and accuracy performances in a wide range of operational conditions. LIDAR Obstacle Warning and Avoidance System (LOWAS) is thus becoming a mature technology with several potential applications to manned and unmanned aircraft. This paper addresses specifically its employment in Unmanned Aircraft Systems (UAS) Sense-and-Avoid (SAA). Small-to-medium size Unmanned Aerial Vehicles (UAVs) are particularly targeted since they are very frequently operated in proximity of the ground and the possibility of a collision is further aggravated by the very limited see-and-avoid capabilities of the remote pilot. After a brief description of the system architecture, mathematical models and algorithms for avoidance trajectory generation are provided. Key aspects of the Human Machine Interface and Interaction (HMI2) design for the UAS obstacle avoidance system are also addressed. Additionally, a comprehensive simulation case study of the avoidance trajectory generation algorithms is presented. It is concluded that LOWAS obstacle detection and trajectory optimisation algorithms can ensure a safe avoidance of all classes of obstacles (i.e., wire, extended and point objects) in a wide range of weather and geometric conditions, providing a pathway for possible integration of this technology into future UAS SAA architectures.

A Laser Obstacle Warning and Avoidance System for Unmanned Aircraft Sense-and-Avoid

<p class="Abstract">This paper presents an overview of the research activities performed to develop a new scaled variant of the Laser Obstacle Avoidance and Monitoring (LOAM) system for small-to-medium size Unmanned Aircraft (UA) platforms. This LOAM variant (LOAM+) is proposed as one of the non-cooperative sensors employed in the UA Sense-and-Avoid (SAA) system. After a brief description of the LOAM system architecture, the mathematical models developed for obstacle avoidance and calculation of alternative flight path are presented. Additionally, a new formulation is adopted for defining the uncertainty volumes associated with the detected obstacles. Simulation case studies are carried out to evaluate the performances of the avoidance trajectory generation and optimisation algorithms, which demonstrate the ability of LOAM+to effectively detect and avoid fixed low-level obstacles in the intended path.</p>

LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft

The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in low-level flying platforms such as helicopters and small-to-medium size Unmanned Aircraft (UA). The Laser Obstacle Avoidance Marconi (LOAM) system is one of such systems, which was jointly developed and tested by SELEX-ES and the Italian Air Force Research and Flight Test Centre. The system was originally conceived for military rotorcraft platforms and, in this paper, we briefly review the previous work and discuss in more details some of the key development activities required for integration of LOAM on UA platforms. The main hardware and software design features of this LOAM variant are presented, including a brief description of the system interfaces and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection, classification and avoidance. In particular, the paper focuses on the algorithm proposed for optimal avoidance trajectory generation in UA applications.

LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft

The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in low-level flying platforms such as helicopters and small-to-medium size Unmanned Aircraft (UA). The Laser Obstacle Avoidance Marconi (LOAM) system is one of such systems, which was jointly developed and tested by SELEX-ES and the Italian Air Force Research and Flight Test Centre. The system was originally conceived for military rotorcraft platforms and, in this paper, we briefly review the previous work and discuss in more details some of the key development activities required for integration of LOAM on UA platforms. The main hardware and software design features of this LOAM variant are presented, including a brief description of the system interfaces and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection, classification and avoidance. In particular, the paper focuses on the algorithm proposed for optimal avoidance trajectory generation in UA applications.

Helicopter miniaturized and low-cost obstacle warning system

This paper reports on a novel development of a miniaturized and low-cost near-field obstacle warning system for helicopters based on an adapted electronically steerable, automotive radar. This system is intended to be used as a flight aid to enhance situational awareness and flight safety by detecting and informing the pilot about obstacles in the near vicinity of the helicopter. The activities described herein are performed in the frame of a research project partially funded by the German Federal Ministry of Economics and Technology. Between January 2010 and March 2012 the system concept was elaborated and a first prototype of the sensor system was developed and successfully tested both in ground and flight tests. This paper will describe the system concept, its design considerations and it will present first test results.

Helicopter Near-Field Obstacle Warning System Based on Low-Cost Millimeter-Wave Radar Technology

This paper describes the specific development of a planar and especially low-cost near-field obstacle warning sensor system for helicopters based on an adapted electronically steerable automotive radar. All system components, from the antenna arrays, the RF modules, to the baseband processing, the signal processing algorithms, and 3-D data visualization were developed and a complete system prototype was built. Ground-based system field trials (static and dynamic sensor tests) were successfully performed during which typical obstacles like overhead power lines, trees, and poles were detected and visualized. In addition, algorithms for geo-referencing of the sensor movements and the detected obstacles were developed and verified.

Laser-based obstacle warning system for helicopters

Laser-based obstacle warning system for helicopters

Wire Obstacle Warning System: A Real-Time Airborne Sensor For Automatic Detection And Recognition Of Wirelike Objects

A sensor has been designed to provide real-time detection and recognition of 3 mm wires at range of 300 meters during nighttime helicopter flight operations. An Army-sponsored program to demonstrate such automatic wire detection and warning for Nap-of-the-Earth (NOE) helicopter missions is currently in progress. Wire or wirelike objects are electro-optically detected and then recognized by a pattern recognition technique. The recognition algorithm is accomplished within 50 msec of the first wire detection indication. A flyable exploratory development wire obstacle warning system model, consisting of a scanning laser transmitter, electro-optical receiver, real-time processor, and display unit is described.