Path Guidance Research Articles

Design, implementation and flight testing of advanced RNP to SBAS LPV approaches in Germany

The recent publication of the advanced Required Navigation Performance (RNP) specifications enable constantly precise aircraft path guidance without demanding expensive equipment and crew certification from the operator. Combined with the operational roll-out of satellite based regional augmentation for Global Navigation Satellite Systems (GNSS), it enables new possibilities such as implementing instrument approach procedures at airports, whose location previously forbade such. Here, we design and flight test two advanced RNP procedures at the airports of Saarbrücken and Egelsbach containing a fixed radius turn which terminates at the final approach fix of a 3D guided final. Results show that the track can be followed with a precision of below 0.1 nautical miles both in manual and in automatic flight with a light piston twin aircraft and with a fast business jet. Effectively, the procedures presented in this paper decouple Saarbrücken airport from French airspace and Egelsbach airport from the high density traffic of the Frankfurt (Main) International control zone.

The Macroeconomic Effects of the Federal Reserve's Unconventional Monetary Policies

After reaching the effective lower bound for the federal funds rate in late 2008, the Federal Reserve turned to two unconventional policy tools -- quantitative easing and increasingly explicit and forward-leaning guidance for the future path of the federal funds rate -- in order to provide additional monetary policy accommodation. We use survey data from the Blue Chip Economic Indicators to infer changes in private-sector perceptions of the implicit interest rate rule that the Federal Reserve would use following liftoff from the effective lower bound. Using our estimates of the changes over time in private expectations for the implicit policy rule, and estimates of the effects of the Federal Reserve's quantitative easing programs on term premiums derived from other studies, we simulate the FRB/US model to assess the actual economic stimulus provided by unconventional policy since early 2009. Our analysis suggests that the net stimulus to real activity and inflation was limited by the gradual nature of the changes in policy expectations and term premium effects, as well as by a persistent belief on the part of the public that the pace of recovery would be much faster than proved to be the case. Our analysis implies that the peak unemployment effect -- subtracting 1¼ percentage points from the unemployment rate relative to what would have occurred in the absence of the unconventional policy actions -- does not occur until early 2015, while the peak inflation effect -- adding ½ percentage point to the inflation rate -- is not anticipated until early 2016.

The Macroeconomic Effects of the Federal Reserve’s Unconventional Monetary Policies

After reaching the effective lower bound for the federal funds rate in late 2008, the Federal Reserve turned to two unconventional policy tools—quantitative easing and increasingly explicit and forward leaning guidance for the future path of the federal funds rate—in order to provide additional monetary policy accommodation. We use survey data from the Blue Chip Economic Indicators to infer changes in private‐sector perceptions of the implicit interest rate rule that the Federal Reserve would use following liftoff from the effective lower bound. Using our estimates of the changes over time in private expectations for the implicit policy rule, and estimates of the effects of the Federal Reserve’s quantitative easing programs on term premiums derived from other studies, we simulate the FRB/US model to assess the actual economic stimulus provided by unconventional policy since early 2009. Our analysis suggests that the net stimulus to real activity and inflation was limited by the gradual nature of the changes in policy expectations and term premium effects, as well as by a persistent belief on the part of the public that the pace of recovery would be much faster than proved to be the case. Our analysis implies that the peak unemployment effect—subtracting 1¼ percentage points from the unemployment rate relative to what would have occurred in the absence of the unconventional policy actions—does not occur until early 2015, while the peak inflation effect—adding ½ percentage point to the inflation rate—is not anticipated until early 2016.

Guidance and control of a scaled-down quad tilt prop PAV

In this paper, a flight control and guidance method for a scaled-down quad tilt prop personal air vehicle (PAV) is presented through simulations and flight tests. The developed scaled-down PAV does not fully transit into a fixed-wing flight mode, but longitudinally tiltable nacelles are used to control the longitudinal translation speed. This design concept can realize a flight maneuver with minimized attitude change because it is only necessary to tilt the nacelles of the propellers and not the attitude angle of the whole body. Although controls of a similar tilt-rotor and quad-tilt vehicles have been reported, a research on a guidance algorithm of a vertical take-off and landing (VTOL) PAV is deficient. Therefore, this paper focuses on the guidance algorithm for the quad tilt prop PAV that requires minimized fluctuation for a passenger. The dynamic behavior and responses of attitude and velocity controllers are identified with reasonable accuracy for a simulated test. Using this model, a guidance algorithm is developed for a circular path to minimize variation of a control input and system states. Through the simulated evaluation against the widely-used proportional navigation guidance algorithm, it was found that the proposed circular path guidance method has better performance in terms of total variation. In addition, through the flight test, the feasibility of the current concept for using the propeller nacelle tilt angle as a control input in forward speed control of a quad tilt prop PAV is proved.

The Macroeconomic Effects of the Federal Reserve's Unconventional Monetary Policies

After reaching the effective lower bound for the federal funds rate in late 2008, the Federal Reserve turned to two unconventional policy tools--quantitative easing and increasingly explicit and forward-leaning guidance for the future path of the federal funds rate--in order to provide additional monetary policy accommodation. We use survey data from the Blue Chip Economic Indicators to infer changes in private-sector perceptions of the implicit interest rate rule that the Federal Reserve would use following liftoff from the effective lower bound. Using our estimates of the changes over time in private expectations for the implicit policy rule, and estimates of the effects of the Federal Reserve's quantitative easing programs on term premiums derived from other studies, we simulate the FRB/US model to assess the actual economic stimulus provided by unconventional policy since early 2009. Our analysis suggests that the net stimulus to real activity and inflation was limited by the gradual nature of the changes in policy expectations and term premium effects, as well as by a persistent belief on the part of the public that the pace of recovery would be much faster than proved to be the case. Our analysis implies that the peak unemployment effect--subtracting 1-1/4 percentage points from the unemployment rate relative to what would have occurred in the absence of the unconventional policy actions--does not occur until early 2015, while the peak inflation effect--adding 1/2 percentage point to the inflation rate--is not anticipated until early 2016.

Path Planning for Visually Impaired People in an Unfamiliar Environment Using Particle Swarm Optimization

Exploring a new environment is a huge challenge for the visually impaired. Hence there is a need for a system that is able to assist them safely during their journey. Here, in this paper, we propose a path planning with predetermined waypoints method using Particle Swarm Optimization (PSO) algorithm. This method computes shortest possible path given the predetermined waypoints from initial position to final position. By using predetermined waypoints which is a collection of coordinates along the pedestrian walkaway, a resulting accessible pedestrian path could be offered to the visually impaired. The system consists of a destination selection process and path planning process. For the destination selection process, a list of available places is given and the user will select the places that they want to visit from the list. The path planning process calculates path length between all nodes which includes predetermined waypoints, start point and final destination using Euclidean distance formula. The PSO algorithm will optimise possible shortest route by minimizing the total cost for path length. The simulation analyses of the proposed method have shown promising results of optimal route for different destinations. Results from this paper will be used further to explore the potential development of path guidance system for the visually impaired people by allowing them to travel independently in an unfamiliar environment.

Intelligent Path Guidance Robot for Visually Impaired Assistance

Visually impaired has limited movement using the classic white cane. Currently, there are many designs for devices that can assist the blind moves better in unfamiliar environment. Then, controllers were applied in the devices’ system so that it can improve the system's efficiency and accuracy in dealing with real-time situations. That's when the intelligent system was introduced in the field to handle nonlinear process of the devices. The purpose of this study is to control steering angle system for an intelligent path guidance robot by using Fuzzy Logic Controller with MATLAB applications. The methods includes the designing of the fuzzy controller for the robot system using Fuzzy logic toolbox, SIMULINK implementation with the results, and the step responses of the system. The fuzzy controller was used to give output for the robot's motor in terms of angle so it can be return back to its track. Two inputs for the system was introduced, error and change in error of the angle of the robot relative to the track given, while the output is the steering angle for the robot. Rule bases for the controller was developed based on the expert knowledge of the system which consist of 9 fuzzy rules. The step responses shows the overshoot, settling time, rise time and peak time after the implementation of the designed Fuzzy Logic Controller in the system.

One-dimensional pairwise CNN for the global alignment of two DNA sequences

The cellular neural network (CNN) is one of the classic artificial neural networks. During the past decades, the one-dimensional CNN models and their applications have not yet been paid enough enthusiasm too. For this reason, this paper proposes a simplified one-dimensional CNN model and then designs a pairwise network using this model to demonstrate its applicability. This pairwise CNN consists of two parallel one-dimensional CNNs, a fixed master and a movable slave. Using this pairwise CNN, an algorithm is developed to perform the global alignment of two DNA sequences. In this algorithm, the slave moves forward step by step, and the cell states of the master are computed in the meanwhile. Based on all the states obtained in all time steps, a state selection array is generated then a global alignment path is determined from this array. Under the guidance of the alignment path, two DNA sequences are globally aligned by inserting blank spaces in the appropriate positions of these two sequences. Experiments on aligning the DNA sequences from the publicly available databases of the NCBI with this method are carried out in this paper and compared with the other two methods. Through evaluating computation time and similarity, these experiments prove that the proposed one-dimensional CNN model is effective, and the alignment algorithm based on a pairwise CNN of the model is efficient, obtaining higher similarity with less computation time than the other two.

Test Noise Procedures for Transport Category and Turbojet Airplanes

Aircraft noise is the chief source of the airport and its peripheral areas. CCAR imposes restriction on specific categories of aircraft and requires more strict measurements of the noise. More scientific measurement method is required to meet the progressively tighter certification standards. Test noise procedures for transport category and turbojet airplanes are analyzed in this paper. The main aspects involved are: test sit requirements, aircraft flight path guidance, aircraft position determination, take off tests, lateral tests and approach tests.

Comparison of Positional Accuracy betweenRTK and RTX GNSS Based on the Autonomous Agricultural Vehicles under Field Conditions

<abstract> <bold><sc>Abstract. </sc></bold>Currently, many systems (machine vision, high resolution remote sensing, global positioning systems, and odometry techniques) have been integrated into agricultural equipment to increase the efficiency, productivity, and safety of the individual in all field activities. This study focused upon assessing a satellite-based localization solution used in straight path guidance of an autonomous vehicle developed for agricultural applications. The autonomous agricultural vehicle was designed and constructed under RHEA (Robot fleets for highly effective agriculture and forestry management) project and is part of a three-unit fleet of similar vehicles. Static tests showed that 99% of all positions are placed within a circle with a 2.9 cm radius centered at the geo-position using real-time satellite corrections (RTX). Dynamic tests between rows demonstrated a mean (N=610) of the standard deviation for real-time base station corrections (RTK) of 1.43 cm and for real-time satellite corrections (RTX) of 2.55 cm. These results demonstrate that the tractor was able to track each straight line with high degree of accuracy. The integration of a Global Navigation Satellite System (GNSS) with sensors (e.g., inertial sensor, altimeters, odometers, etc.) within the vehicle showed the potential of autonomous tractors for expanding agricultural applications utilizing this technology.

An approach to filling firms' knowledge gaps based on organisational knowledge structure

Purpose – The objective of this paper is to propose a practical and operable method to identify and fill organisational knowledge gaps during new product development. Design/methodology/approach – From a microscopic view, this paper introduces the tree-shaped organisational knowledge structure to formalise the knowledge gaps and their internal hierarchical relationships. Based on the organisational knowledge structure, organisational knowledge gaps are identified through tree matching algorithm. The tree-edit-distance method is introduced to calculate the similarity between two organisational knowledge structures for filling knowledge gap. Findings – The proposed tree-shaped organisational knowledge structure can represent organisations' knowledge and their hierarchy relationships in a structured format, which is useful for identifying and filling organisational knowledge gaps. Originality/value – The proposed concept of organisational knowledge structure can quantify organisational knowledge. The approach is valuable for strategic decisions regarding new product development. The organisational knowledge gaps identified with this method can provide real-time and accurate guidance for the product development path. More importantly, this method can accelerate the organisational knowledge gap filling process and promote organisational innovation.

Photometric Evaluation of Steady-Burn Warning Lights in Work Zones

This report documents the efforts and results of several photometric evaluations performed by researchers at the Texas A&amp;M Transportation Institute to assess the performance of steady-burn warning lights in temporary traffic control devices used to delineate the correct travel path in work zones. The research included an assessment of the potential incremental increase in luminance (and benefit of that increase to drivers) during vulnerable driving conditions. These conditions included periods of heavy fog, periods when dirt and grime had accumulated on the channelizing device, and misalignment of warning lights. The researchers found that fog adversely affected the apparent luminance (and thus the visibility distance) of both retroreflective sheeting and warning lights. However, retroreflective sheeting was still likely to be visible at distances needed for purposes of path guidance and delineation, and the use of warning lights was unlikely to provide much additional value to motorists. The researchers also found that the accumulation of dirt and grime on the retroreflective sheeting of drums in Florida work zones did have an impact on device luminance. Although the use of warning lights did increase the overall luminance of channelizing drums, a greater increase in luminance was noted when the drums were clean. Finally, misalignment of lights significantly reduced their photometric value.

Board 535 - Technology Innovations Abstract A Hybrid Approach to Computer-Guided Laparoscopy Training

Introduction/Background Laparoscopic surgery, when performed by a well-trained surgeon, is a remarkably effective procedure that minimizes complications associated with large incisions, operative blood loss and post-operative pain. However, the procedure is more challenging than a conventional surgery due to the restricted vision, hand-eye coordination problems, limited working space, and lack of tactile sensation. These issues make the laparoscopic surgery a very difficult technique for medical students and residents to master. To minimize the potential risks inherent in laparoscopic procedures, effective and innovative training and guidance Methods are needed. The focus of this abstract is a technology that assists in computer-guided minimally invasive surgical training. Some sophisticated training Methods using guided force, or navigation assistance, have been briefly studied in areas such as physical therapy for stroke victims and teaching Japanese calligraphy, and found to be beneficial, especially in conjunction with visual feedback.1-3 Navigational guidance is offered in both neurosurgery and orthopedic surgery, such as through the SpineAssist by Mazor systems.4 Methods Method: We are motivated by the belief that automation-based, guided laparoscopic skills training will lead to improved performance and, ultimately, better surgical outcomes. We have developed a computer-aided surgical trainer (CAST) for laparoscopic skill training.5-7 CAST prototype is a unique mechatronic (mechanical and electronic) device that provides an unlimited range of training exercises using real surgical instruments, with precise performance data collection and analysis tools. This device is perfectly suited to fill the gap between the very expensive virtual reality based trainers, and relatively crude low-cost, box trainers. Computer-based, optimal training path guidance, vision and sensor-based performance data acquisition are capabilities that that set CAST apart from currently available systems. Results: Haptic feedback is given by connecting a small robotic manipulator to surgical instruments. The manipulator exerts force and torque on the devices. The software used in the CAST system has two components: the haptic guidance and the visual guidance systems. The haptic guidancecontroller is implemented using a PID method which provides haptic feedback by applying force when the trainee deviates from the optimal trajectory.8 The controller uses actual position and reference position of the instrument tip, where the actual position is measured by encoders and the reference position is offered by the optimal path generator module. The actual position is also used for the visual guidance system. The visual guidance system uses augmented reality (AR) techniques on the training scenario.9 We map real world coordinates to the image using camera calibration through linear least squares technique.10 This, incorporated with the haptic guidance algorithm, enables us to provide combined force and visual guidance to the trainees. Proper guidance includes displaying the estimated optimal path and instructions on the screen to help the trainees know what to do, and what not to do. Guided training will be validated with through a pilot experimental study in which expertise level of computer-guided trainees will be compared to that of instructor-guided trainees. The system will be tested in an experimental study by comparing the Results of hand-eye coordination and depth perception using the augmented reality trainer versus other systems. Results: Conclusion The potential impact of our proposed work is improved surgical performance and, ultimately, better surgical outcomes. The optimal surgical movement planner and its attendant computer-based guidance will reinforce proper execution of specific tasks.

Haptic guidance interferes with learning to make movements at an angle to stimulus direction

Haptic guidance has been shown to interfere with learning a novel visuo-motor rotation. Here, we ask whether this interference is specific to the learning of visuo-motor transformations or whether it is a more generalized phenomenon of learning spatial movement characteristics. Participants practiced to make movements at an angle of 75° relative to target directions with and without haptic path guidance. Test trials without guidance and without visual feedback revealed poorer performance after haptic guidance practice than in the no-guidance control group, even though during guided practice movement directions were more accurate than during unguided practice. The more precise directions during guided practice were associated with shorter movement latencies than in the control group, suggesting an incomplete rotation of the movement direction relative to the direction of the visual target. A detailed analysis of the first few millimeters of each movement revealed that the initial movement direction was indeed rotated too little, and the correct direction was adopted only gradually under the influence of haptic guidance. These findings support the perspective on motor learning as a process that is driven by consequent improvements of performance and that is compromised by factors that serve to improve performance even without learning. Haptic guidance is one such factor.

Congestion-Aware Multi-Agent Path Planning: Distributed Algorithm and Applications

This paper proposes a method for multi-agent path planning on a road network in the presence of congestion. We suggest a distributed method to find paths for multiple agents by introducing a probabilistic path choice achieving global goals such as the user equilibrium or the social optimum. This approach, which shows that the global goals can be achieved by local processing using only local information, can be parallelized and sped-up using massive parallel processing. The probabilistic assignment reliably copes with the case of random choices of unidentified agents or random route changes of agents who ignore our path guidance. We provide the analytical result on convergence and running time. We demonstrate and evaluate our algorithm by an implementation using asynchronous computation on multi-core computers.

A New Avionics-Based GNSS Integrity Augmentation System: Part 2 – Integrity Flags

This paper presents the second part of the research activities carried out to develop a novel Global Navigation Satellite System (GNSS) Avionics-Based Integrity Augmentation (ABIA) system for manned and Unmanned Aerial Vehicle (UAV) applications. The ABIA system's architecture was developed to allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In more detail, our novel ABIA system addresses all four cornerstones of GNSS integrity augmentation in mission- and safety-critical avionics applications: prediction (caution flags), avoidance (optimal flight path guidance), reaction (warning flags) and correction (recovery flight path guidance). Part 1 (Sabatini et al., 2012) presented the ABIA concept, architecture and key mathematical models used to describe GNSS integrity issues in aircraft applications. This second part addresses the ABIA caution and warning integrity flags criteria and presents the results of a simulation case study performed on the TORNADO Interdiction and Strike (IDS) aircraft.

The Design of Intelligent Guidance System Model Based on Network Teaching Platform

In this paper, some researches have made on students’ independent learning, employing CDIO International engineering education idea and the theory of association path method and guidance, an intelligent guidance system model based on network teaching platform was designed. The system according to the students frequent access path, learning records and other information, applies Apriori algorithm for data mining, and integrates uploading new points of knowledge and old knowledge, to provide students a learning guidance and help students improve their learning efficiency.

가상계측기반 실시간 영상유도 자동비행 시스템 구현 및 무인 로터기를 이용한 비행시험

This paper investigates the implementation and flight test of realtime vision guided autopilot system based on virtual instrumentation platform. A graphical design process via virtual instrumentation platform is fully used for the image processing, communication between systems, vehicle dynamics control, and vision coupled guidance algorithms. A significatnt ojective of the algorithm is to achieve an environment robust autopilot despite wind and an irregular image acquisition condition. For a robust vision guided path tracking and hovering performance, the flight path guidance logic is combined in a multi conditional basis with the position estimation algorithm coupled with the vehicle attitude dynamics. An onboard flight test equipped with the developed realtime vision guided autopilot system is done using the rotary UAV system with full attitude control capability. Outdoor flight test demonstrated that the designed vision guided autopilot system succeeded in UAV's hovering on top of ground target within about several meters under geenral windy environment.

Robot-assisted intermanual transfer of handwriting skills

We examined whether intermanual transfer of fine motor skills can be facilitated by training in a virtual environment. We focused on three types of assistance: visual – subjects could see a reference template on a computer screen – and two variants of haptic assistance. Subjects held a planar robot manipulandum and were required to write isolated cursive letters of an approximate size of 5cm. Therefore, the task was similar to writing on a horizontal blackboard. The robot generated forces that were directed either towards the reference template (path guidance) or towards the reference trajectory (trajectory guidance). The training protocol consisted of three assisted exercise sessions on three consecutive days. Performance on the following day was tested to assess retention. After training, the improvement in trajectory shape was only significant in trajectory guidance and, to a lesser extent, visual guidance. Path guidance exhibited no significant improvement. These effects were substantially retained one day after the end of training. Similar effects were observed in shape variability. Furthermore, all training modalities caused a reduction in movement duration, but no significant differences were observed among groups. These results suggest that robot assistance may be beneficial for improving intermanual transfer, but inclusion of temporal information in the guidance strategy is essential for learning to take place.

2-Dimensional SVFC Application in Path Planning of Mobile Robots

A 2-dimensional single variable fuzzy controller (SVFC) is introduced to achieve the path planning for mobile robots. With fusing some fuzzy and uncertain information obtained from distance and angle sensors, and invoking the corresponding fuzzy logic inference, this SVFC can output the action instruction, which then determines the behavior control, realizing the optimal non-collision path planning for the mobile robots. The essential jobs in this whole design process consist of the defining the fuzzy sets, discrete grades and membership functions for the input and output parameters, establishing the rules for fuzzy controller, and evaluating the fuzzy control response. Due to the complex computation of the high dimension matrixes achieved from the SVFC, an off-line inquiring table scheme is proposed to gain the inference response, which strictly follows the Mamdani inference rules, viz. Max-Min integrated theory, a practical fuzzy control response table is presented in sequence. Moreover, after constituting the working environmental model, the numerical simulation is implemented to estimate the performance of this fuzzy control system. The simulation result shows that the SVFC leads to the intelligent, simple, and accurate path guidance for mobile robots, indicating the behavior control and realizing the navigation tasks.