Proceedings of the Augmented VIsual Display (AVID) Research Workshop

The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics

Insect inspired behaviours for the autonomous control of mobile robots

Animals navigate through various uncontrolled environments with seemingly little effort. Flying insects, especially, are quite adept at manoeuvring in complex, unpredictable and possibly hostile environments. Through both simulation and real-world experiments, we demonstrate the feasibility of equipping a mobile robot with the ability to navigate a corridor environment, in real time, using principles based on insect-based visual guidance. In particular we have used the bees&rsquo; navigational strategy of measuring object range in terms of image velocity. We have also shown the viability and usefulness of various other insect behaviours: (i) keeping walls equidistant, (ii) slowing down when approaching an object, (iii) regulating speed according to tunnel width, and (iv) using visual motion as a measure of distance travelled.<br /

An optical flow-based sensing system for reactive mobile robot navigation

This work discusses the use of optical flow to generate the sensorial information a mobile robot needs to react to the presence of obstacles when navigating in a non-structured environment. A sensing system based on optical flow and time-to-collision calculation is here proposed and experimented, which accomplishes two important paradigms. The first one is that all computations are performed onboard the robot, in spite of the limited computational capability available. The second one is that the algorithms for optical flow and time-to-collision calculations are fast enough to give the mobile robot the capability of reacting to any environmental change in real-time. Results of real experiments in which the sensing system here proposed is used as the only source of sensorial data to guide a mobile robot to avoid obstacles while wandering around are presented, and the analysis of such results allows validating the proposed sensing system

Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency

A novel mobile robots 3D-perception obstacle regions method in indoor environment based on Improved Salient Region Extraction (ISRE) is proposed. This model acquires the original image by the Kinect sensor and then gains Original Salience Map (OSM) and Intensity Feature Map (IFM) from the original image by the salience filtering algorithm. The IFM was used as the input neutron of PCNN. In order to make the ignition range more exact, PCNN ignition pulse input was further improved as follows: point multiplication algorithm was taken between PCNN internal neuron and binarization salience image of OSM; then we determined the final ignition pulse input. The salience binarization region abstraction was fulfilled by improved PCNN multiple iterations finally. Finally, the binarization area was mapped to the depth map obtained by Kinect sensor, and mobile robot can achieve the obstacle localization function. The method was conducted on a mobile robot (Pioneer3-DX). The experimental results demonstrated the feasibility and effectiveness of the proposed algorithm

Designing Automated Guided Vehicle Using Image Sensor

Automated guided vehicles (AGV) are one of the greatest achievements in the field of mobile robotics. Without continuous guidance from a human they navigate on desired path thus completing various tasks, e.g. fork lifting objects, towing, and product transportation inside manufacturing firm. Their development can revolutionize the world in the sense of fool proof navigation and accurate maneuvering. Though most of the presently the AGV work in a retrofitted environment, work space as they require some identification for tracing their guide path, works are going on developing such AGVs which are dynamic in sense of navigation and whose locomotion is not limited to just a retrofitted workspace. The aim of this work was developing such a natural feature AGV which takes visual input in the form images and gains detailed object, obstacle, landmark, identification to decide its guide path. The AGV set up developed, used a commercial electric motor based car ‘Reva i’, as chassis which was fitted with camera to take real time input and resolve it using segmentation and image processing techniques to reach a decision of driving controls. These controls were communicated, or better imparted to vehicle using parallel port of computer to servo motors, which in turn controlled the motion of vehicle. The work was focused more on dynamically controlling the vehicle using refinement of driving mechanism (hardware), however it could be assisted using better segmentation and obstacle detection algorithm. All the retro-fitting and codes were developed in such a way that they could be improved at any stage of time. The results could be enhanced if a better stereoscopic camera were used with a dedicated cpu with better graphics capability. This vision based AGV can revolutionize the mobile robotics world, including systems where a human driver is required to take decisions on the basis of visualized condition

Second CLIPS Conference Proceedings, volume 1

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems

Simulation in Automated Guided Vehicle System Design

The intense global competition that manufacturing companies face today results in an increase of product variety and shorter product life cycles. One response to this threat is agile manufacturing concepts. This requires materials handling systems that are agile and capable of reconfiguration. As competition in the world marketplace becomes increasingly customer-driven, manufacturing environments must be highly reconfigurable and responsive to accommodate product and process changes, with rigid, static automation systems giving way to more flexible types. Automated Guided Vehicle Systems (AGVS) have such capabilities and AGV functionality has been developed to improve flexibility and diminish the traditional disadvantages of AGV-systems. The AGV-system design is however a multi-faceted problem with a large number of design factors of which many are correlating and interdependent. Available methods and techniques exhibit problems in supporting the whole design process. A research review of the work reported on AGVS development in combination with simulation revealed that of 39 papers only four were industrially related. Most work was on the conceptual design phase, but little has been reported on the detailed simulation of AGVS. Semi-autonomous vehicles (SA V) are an innovative concept to overcome the problems of inflexible -systems and to improve materials handling functionality. The SA V concept introduces a higher degree of autonomy in industrial AGV -systems with the man-in-the-Ioop. The introduction of autonomy in industrial applications is approached by explicitly controlling the level of autonomy at different occasions. The SA V s are easy to program and easily reconfigurable regarding navigation systems and material handling equipment. Novel approaches to materials handling like the SA V -concept place new requirements on the AGVS development and the use of simulation as a part of the process. Traditional AGV -system simulation approaches do not fully meet these requirements and the improved functionality of AGVs is not used to its full power. There is a considerflble potential in shortening the AGV -system design-cycle, and thus the manufacturing system design-cycle, and still achieve more accurate solutions well suited for MRS tasks. Recent developments in simulation tools for manufacturing have improved production engineering development and the tools are being adopted more widely in industry. For the development of AGV -systems this has not fully been exploited. Previous research has focused on the conceptual part of the design process and many simulation approaches to AGV -system design lack in validity. In this thesis a methodology is proposed for the structured development of AGV -systems using simulation. Elements of this methodology address the development of novel functionality. The objective of the first research case of this research study was to identify factors for industrial AGV -system simulation. The second research case focuses on simulation in the design of Semi-autonomous vehicles, and the third case evaluates a simulation based design framework. This research study has advanced development by offering a framework for developing testing and evaluating AGV -systems, based on concurrent development using a virtual environment. The ability to exploit unique or novel features of AGVs based on a virtual environment improves the potential of AGV-systems considerably.University of Skovde. European Commission for funding the INCO/COPERNICUS Projec

Platooning-based control techniques in transportation and logistic

This thesis explores the integration of autonomous vehicle technology with smart manufacturing systems. At first, essential control methods for autonomous vehicles, including Linear Matrix Inequalities (LMIs), Linear Quadratic Regulation (LQR)/Linear Quadratic Tracking (LQT), PID controllers, and dynamic control logic via flowcharts, are examined. These techniques are adapted for platooning to enhance coordination, safety, and efficiency within vehicle fleets, and various scenarios are analyzed to confirm their effectiveness in achieving predetermined performance goals such as inter-vehicle distance and fuel consumption. A first approach on simplified hardware, yet realistic to model the vehicle's behavior, is treated to further prove the theoretical results. Subsequently, performance improvement in smart manufacturing systems (SMS) is treated. The focus is placed on offline and online scheduling techniques exploiting Mixed Integer Linear Programming (MILP) to model the shop floor and Model Predictive Control (MPC) to adapt scheduling to unforeseen events, in order to understand how optimization algorithms and decision-making frameworks can transform resource allocation and production processes, ultimately improving manufacturing efficiency. In the final part of the work, platooning techniques are employed within SMS. Autonomous Guided Vehicles (AGVs) are reimagined as autonomous vehicles, grouping them within platoon formations according to different criteria, and controlled to avoid collisions while carrying out production orders. This strategic integration applies platooning principles to transform AGV logistics within the SMS. The impact of AGV platooning on key performance metrics, such as makespan, is devised, providing insights into optimizing manufacturing processes. Throughout this work, various research fields are examined, with intersecting future technologies from precise control in autonomous vehicles to the coordination of manufacturing resources. This thesis provides a comprehensive view of how optimization and automation can reshape efficiency and productivity not only in the domain of autonomous vehicles but also in manufacturing