Event-Based Obstacle Detection with Commercial Lidar

Computerized obstacle detection for moving vehicles is becoming more important as vehicle manufacturers make their systems more autonomous and safe. However, obstacle detection must operate quickly in dynamic environments such as driving at highway speeds. A unique obstacle detection system using 3D changes in the environment is proposed. Furthermore, these 3D changes are shown to contain sufficient information for avoiding obstacles. To make the system easy to integrate onto a vehicle, additional processing is implemented to remove unnecessary dependencies. This system provides a method for obstacle detection that breaks away from typical systems to be more efficient

Sensor Characterization and Signal Fusion for InstantEye

The practicality and effectiveness of using a TerraRanger Duo—a parallel sonar and infrared time-of-flight distance sensor—payload for obstacle detection is investigated for use with Physical Science Inc.’s InstantEye drone. A Python program was developed to interface with the serial data output before comparing the sensor’s empirical performance against its data sheet. The two signals from the distinct sensor modules, each with their characterized strengths and weaknesses, were then fused with a Kalman filter. This was further refined by imposing conditional weighting based on the known sensor characteristics. The filter output, with conditional corrections, was able to accurately track a single object’s position and velocity within a maximum range of 14 meters

Aerial obstacle detection with 3D mobile devices

In this paper, we present a novel approach for aerial obstacle detection (e.g. branches or awnings) using a 3D smartphone in the context of the visually impaired (VI) people assistance. This kind of obstacles are especially challenging because they cannot be detected by the walking stick or the guide dog. The algorithm captures the 3D data of the scene through stereo vision. To our knowledge, this is the first work that presents a technology able to obtain real 3D measures with smartphones in real time. The orientation sensors of the device (magnetometer and accelerometer) are used to approximate the walking direction of the user, in order to look for the obstacles only in such direction. The obtained 3D data are compressed and then linearized for detecting the potential obstacles. Potential obstacles are tracked in order to accumulate enough evidence to alert the user only when a real obstacle is found. In the experimental section, we show the results of the algorithm in several situations using real data and helped by VI users.J.M. Sáez and M.A. Lozano are supported by the University of Alicante research grant GRE10-21. F. Escolano is supported by the project TIN2012-32839 of the Spanish Government

Evaluation of the Effectiveness of Radar Obstacle Detection Systems when Used on Industrial Lift Trucks

This study addresses the application and the effectiveness of radar obstacle sensors for forklift trucks during reverse travel. Two different discriminating radar obstacle sensors with different outputs are evaluated. This study reviews the safety of human exposure to emissions from these radar sensors; documents the field of view obtained from experiments with the two systems; gives the results from experiments with sensors on lift trucks. The influence of obstacle reflectivity, composition and area on the size and shape of the radar detection zone are discussed. An experimental setup for measuring position and velocity of the obstacle crossing the truck path is described. The combination of obstacle sensors required for full coverage of the back of the lift trucks and the mounting height and angle are discussed

OBSTACLE DETECTION AND NAVIGATION OF AUTONOMOUS ROBOT

This report presents an obstacle detect autonomous mobile robot. Robot used an Atmega 32 microcontroller as its brain. Atmega 32 receives input from Ultrasonic Distance Meter (UDM). Some computations are performed on this input and a control signal is generated to control the robot\u27s position. This control signal is generated through a PWM signal. which is implemented in the microcontroller. Afterwards, microcontroller was programmed in C language using a AVR Studio4 compiler

Multirotor UAS Sense and Avoid with Sensor Fusion

In this thesis, the key concepts of independent autonomous Unmanned Aircraft Systems (UAS) are explored including obstacle detection, dynamic obstacle state estimation, and avoidance strategy. This area is explored in pursuit of determining the viability of UAS Sense and Avoid (SAA) in static and dynamic operational environments. This exploration is driven by dynamic simulation and post-processing of real-world data. A sensor suite comprised of a 3D Light Detection and Ranging (LIDAR) sensor, visual camera, and 9 Degree of Freedom (DOF) Inertial Measurement Unit (IMU) was found to be beneficial to autonomous UAS SAA in urban environments. Promising results are based on to the broadening of available information about a dynamic or fixed obstacle via pixel-level LIDAR point cloud fusion and the combination of inertial measurements and LIDAR point clouds for localization purposes. However, there is still a significant amount of development required to optimize a data fusion method and SAA guidance method

Generalized Centrifugal Force Model for Pedestrian Dynamics

A spatially continuous force-based model for simulating pedestrian dynamics is introduced which includes an elliptical volume exclusion of pedestrians. We discuss the phenomena of oscillations and overlapping which occur for certain choices of the forces. The main intention of this work is the quantitative description of pedestrian movement in several geometries. Measurements of the fundamental diagram in narrow and wide corridors are performed. The results of the proposed model show good agreement with empirical data obtained in controlled experiments.Comment: 10 pages, 14 figures, accepted for publication as a Regular Article in Physical Review E. This version contains minor change