Highly efficient Localisation utilising Weightless neural systems

Efficient localisation is a highly desirable property for an autonomous navigation system. Weightless neural networks offer a real-time approach to robotics applications by reducing hardware and software requirements for pattern recognition techniques. Such networks offer the potential for objects, structures, routes and locations to be easily identified and maps constructed from fused limited sensor data as information becomes available. We show that in the absence of concise and complex information, localisation can be obtained using simple algorithms from data with inherent uncertainties using a combination of Genetic Algorithm techniques applied to a Weightless Neural Architecture

A kalman filter for validate points and areas of constant depth in the acquisition of the profiles surfaces

This paper presents multisensor fusion techniques for the acquisition of the profile of surfaces with minimum error using low cost ultrasonic sensors. These surfaces are composed by areas with different depths, corners and specular surfaces. To minimize the constraints of sonar sensors, it was developed dedicated software and hardware, as well as an empirical model was obtained from real data. This model is based in two proposed concepts: Points of Constant Depth (PCD) and Areas of Constant Depth (ACD). Having this sonar model in mind, four sensor fusion techniques are used separately to validate the PCDs and decide the ACDs: average and variance, a simplified kalman filter and heuristic method based in rules. In this work a PUMA 560 manipulator was equipped with a CCD video camera and four ultrasonic sensors on the wrist, to acquire data for internally representation of the geometry of the part’s surface, exploiting the mobility of the robot. The CCD camera defines the working area while the ultrasonic sensors enable the acquisition of the surface profile

Acquisition the profile of surfaces with complementary sensor fusion techniques

This paper presents complementary sensor fusion techniques for the acquisition of the profile of surfaces with minimum error using low cost sensors ultrasonic sensors. These surfaces are composed by areas with different depths, corners and specular surfaces. To minimize the constraints of sonar sensors, it was developed dedicated software and hardware, as well as an empirical model was obtained from real data. This model is based in two proposed concepts: Points of Constant Depth (PCD) and Areas of Constant Depth (ACD). Having this sonar model in mind, four sensor fusion techniques are used separately to validate the PCDs and decide the ACDs: average and variance, fuzzy controller and heuristic method based in rules. In this work a PUMA 560 manipulator was equipped with a CCD video camera on the shoulder and four ultrasonic sensors on the wrist, to acquire data to model the geometry of the part’s surface, exploiting the mobility of the robot. The CCD camera view defines the working area, while the ultrasonic sensors enable the acquisition of the surface profile. For the acquisition of the profile of surfaces with a minimum error different and complementary sensor fusion techniques are implemented and applied separately, namely the average and variance, kalman filter, fuzzy controller and heuristic method based in rules

Design, Construction, Energy Modeling, and Navigation of a Six-Wheeled Differential Drive Robot to Deliver Medical Supplies inside Hospitals

Differential drive mobile robots have been the most ubiquitous kind of robots for the last few decades. As each of the wheels of a differential drive mobile robot can be controlled, it provides additional flexibility to the end-users in creating new applications. These applications include personal assistance, security, warehouse and distribution applications, ocean and space exploration, etc. In a clinic or hospital, the delivery of medicines and patients’ records are frequently needed activities. Medical personnel often find these activities repetitive and time-consuming. Our research was to design, construct, produce an energy model, and develop a navigation control method for a six-wheeled differential drive robot designed to deliver medical supplies inside the hospital. Such a robot is expected to lessen the workload of medical staff. Therefore, the design and implementation of a six-wheeled differential drive robot with a password-protected medicine carrier were presented. This password-protected medicine carrier ensures that only the authorized medical personnel can receive medical supplies. The low-cost robot base and the medicine carrier were built in real life. Besides the actual robot design and fabrication, a kinematic model for the robot was developed, and a navigation control algorithm to avoid obstacles was implemented using MATLAB/Simulink. The kinematic modeling is helpful for the robot to achieve better energy optimization. To develop the object avoidance algorithm, we investigated the use of the Robot Operating System (ROS) and the Simultaneous Localization and Mapping (SLAM) algorithm for the implementation of the mapping and navigation of a robotic platform named TurtleBot 2. Finally, using the Webot robot simulator, the navigation of the six-wheeled mobile robot was demonstrated in a hospital-like simulation environment

A systematic review of perception system and simulators for autonomous vehicles research

This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.This work was partially supported by DGT (ref. SPIP2017-02286) and GenoVision (ref. BFU2017-88300-C2-2-R) Spanish Government projects, and the “Research Programme for Groups of Scientific Excellence in the Region of Murcia" of the Seneca Foundation (Agency for Science and Technology in the Region of Murcia – 19895/GERM/15)

Redirection Concept of Autonomous Mobile Robot HY-SRF05 Sensor to Reduce The Number of Sensors

The autonomous mobile robot can move around and avoid obstacles in front by itself. The data generated by the sensors is processed using an algorithm and specific methods to determine the movement of the robot. Ultrasonic sensor installed on the Mobile robot with a straight forward position. Ultrasonic sensor can detect the obstacle 30 degrees in front, which creates the blank area of the sensor between two ultrasonic sensors. Ultrasonic sensors installed at many points to reduce that blank area. This paper offers the concept of two ultrasonic sensor redirection by mounting it tilted so when it is drawn will form a right triangle that  the concept  of trigonometry  applied. The results of the approximate distance between the obstacle sensor becomes the hypotenuse, while the distance between the two sensors already obtained so that the distance between the mobile robot with the real obstacle can be calculated. The mechanism of mobile robot  movement mimics  the movement of agricultural tractors. The test results showed that the optimum angle between the two ultrasonic sensors is 35 to 55 degree. Redirection ultrasonic sensors will reduce approximately 42% of the number of sensors that are installed straight ahead