A Flight Management System (FMS) performs 4 Dimensional flight planning / Lateral Planning (Calculation of the latitude and longitudes of waypoints), Vertical Planning (Calculation of the altitudes of waypoints) and Temporal Planning(Calculation of Estimated Time of Arrival). Correct and accurate calculation of4D flight path and then guiding the pilot/airplane to track the route in specified accuracy limits in terms of lateral (i.e Required Navigational Performance RNP), vertical (Reduced Vertical Seperation Minima RVSM), and time (Required Time of Arrival RTA) is what FMS performs in brief. Any deviation of planned input values versus actual input values, especially during the emergency cases (i.e burning outoneof engines etc.), causes the aircraft to deviate the plan and requires replanning now taking into consideration the currentsituation. In emergency situations especially in Oceaning Flights (flights whose cruise phase lasts more than 5 hour is called as &ldquo / Oceaning Flights&rdquo / ) Optimum Cruise Phase Flight Route Planning plays a vital role. In avionics domain &ldquo / Optimum&rdquo / does not mean &ldquo / shortest path&rdquo / mainly due to the effect of weather data as wind speed and direction directly affects the groundspeed. In the scope of the current thesis, an algorithm employing dynamic programming paradigms will be designed and implemented to find the optimum flight route planning. A top down approach by making use of aircraft route planning ontology will be implemented to fill the gap between the flight plan specific domain knowledge and optimization techniques employed. Where as the algorithm will be generic by encapsulating the aircraft&rsquo / s performance characteristics / it will be evaluated on C-130 aircraft.

Context: Unmanned Aerial Vehicles are being widely being used for various scientific and non-scientific purposes. This increases the need for effective and efficient path planning of Unmanned Aerial Vehicles.Two of the most commonly used methods are the A-star algorithm and Mixed Integer Linear Programming.Objectives: Conduct a simulation experiment to determine the performance of A-star algorithm and Mixed Integer Linear Programming for path planning of Unmanned Aerial Vehicle in a simulated environment.Further, evaluate A-star algorithm and Mixed Integer LinearProgramming based computational time and computational space to find out the efficiency. Finally, perform a comparative analysis of A star algorithm and Mixed Integer Linear Programming and analyse the results.Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of Objectives: Conduct a simulation experiment to determine the performance of A-star algorithm and Mixed Integer Linear Programming for path planning of Unmanned Aerial Vehicle in a simulated environment.Further, evaluate A-star algorithm and Mixed Integer LinearProgramming based computational time and computational space to find out the efficiency. Finally, perform a comparative analysis of A star algorithm and Mixed Integer Linear Programming and analyse the results.Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of these methods. These methods are then implemented on these test scenarios and the computational times for both the scenarios were observed.A hypothesis is proposed to analyse the results. A performance evaluation of these methods is done and they are compared for a better performance in the generated environment. Results: It is observed that the efficiency of A-star algorithm andMILP algorithm when no obstacles are considered is 3.005 and 12.03functions per second and when obstacles are encountered is 1.56 and10.59 functions per seconds. The results are statistically tested using hypothesis testing resulting in the inference that there is a significant difference between the computation time of A-star algorithm andMILP. Performance evaluation is done, using these results and the efficiency of algorithms in the generated environment is obtained.Conclusions: The experimental results are analysed, and the Conclusions: The experimental results are analysed, and the efficiencies of A-star algorithm and Mixed Integer Linear Programming for a particular environment is measured. The performance analysis of the algorithm provides us with a clear view as to which algorithm is better when used in a real-time scenario. It is observed that Mixed IntegerLinear Programming is significantly better than A-star algorithm.

BACKGROUND: The integration of robotics, and mixed reality has ushered in a substantial revolution within the realm of Industry 4.0. The incorporation of robots into the manufacturing sector plays a pivotal role in enhancing productivity, in which humans and robots collaborate with each other. However, the current robotic system operates within predefined pathways exclusively, lacking an automated mechanism for identifying obstacle free routes to facilitate the movement of robot . Also, in the Human Robot Collaboration , there exists a deficiency in visualising robot motion and status, consequently arise safety vulnerabilities for human operators. OBJECTIVES: This thesis aims to implement a pathfinding algorithm for the robot movement using a mixed reality environment. This Mixed Reality application is used to assign targets and handle obstacles in the robot movement path. The visual guide about the robot movement path, the state of the robot and the tasks to the user that will be displayed using MR. METHODS : In pursuit of the thesis objectives, a Mixed Reality environment was developed using Unity alongside MRTK plugins. Within this framework, an A Star pathfinding algorithm was implemented, facilitating the computation of obstacle free routes between source and destination points. This MR environment not only visualises the trajectory of the robot 's movement but also presents robot status updates and an intuitive interface for operator robot communication. The development process involved creating essential code using C# within the Visual Studio IDE. This code was subsequently deployed onto the HoloLens 2, the designated hardware device for MR applications. The positioning and alignment of virtual objects in relation to the physical world were achieved using the QR code methodology. In this context, source and destination points for the robot 's movement were symbolised as targets, while obstacles were represented by square game objects. For the control and communication of the ABB GoFa C RB 15000 robot, RAPID code was devised within Robot Studio.To guide the thesis, a constructivist philosophical paradigm was embraced, aiming to enhance efficacy. Ethical considerations were scrupulously considered for data collection, prioritising user privacy within the MR environment. Furthermore, commitment to sustainability was maintained throughout the thesis work, yielding environmental, economic, and societal advantages. ANALYSIS: The project that was developed underwent analysis through the scenarios, including both obstacle laden and obstacle free pathfinding situations. The A Star pathfinding algorithm, effectively calculated the obstacle free routes between targets and accomplished designated robotic tasks. This implementation not only offered visual path guidance but also supplied status updates. The analysis process involved observations, video recordings, and documentation. The findings indicated that the created Mixed Reality environment indeed enhanced safety and cognitive ergonomics for the operator. This section also outlines the industrial applications of the project developed. CONCLUSION: Successful development of a Mixed Reality environment has been achieved, aimed at enabling automated obstacle free pathfinding. This environment also offers visualisations for path and status information, with the goal of enhancing safety and cognitive ergonomics in Human Robot Collaboration. Throughout this thesis endeavour, strong attention has been paid to ethical considerations and sustainability.