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This thesis explores the possibilities of creating landscapes through procedural means within the game engine Unreal Engine 5. The aim is to provide a flexible procedural landscape tool that doesn't limit the user and that is compatible with existing systems in the engine. The research questions focuses on comparison to other work regarding landscape generation and generation of procedural roads. The process to achieve this was done through extensive implementation adding modules that both builds upon and adds to the source code. The implementation was divided into five major components, which was noise generation for terrain, biotope interpolation, asset distribution, road generation and a user interface. Perlin noise, utilizing Fractal Brownian Motion were a vital part of generating terrain with varying features. For interpolation a modified version of Lowpass Gaussian filtering was implemented in order to blend biotope edges together. Asset distribution and road generation were implemented in a way that uses pseudo-randomness combined with heuristics. The user interface was done to tie everything together for testing. The results shows potential for assisting in procedural landscape creation with a large amount of freedom in customization. There is however flaws in some aspects, namely the interpolation methods suffer from clear visual artefacts. Whether it is suitable for professional standards remains to be fully proven objectively as the testing in this thesis work was limited.

This thesis explores the possibilities of creating landscapes through procedural means within the game engine Unreal Engine 5. The aim is to provide a flexible procedural landscape tool that doesn't limit the user and that is compatible with existing systems in the engine. The research questions focuses on comparison to other work regarding landscape generation and generation of procedural roads. The process to achieve this was done through extensive implementation adding modules that both builds upon and adds to the source code. The implementation was divided into five major components, which was noise generation for terrain, biotope interpolation, asset distribution, road generation and a user interface. Perlin noise, utilizing Fractal Brownian Motion were a vital part of generating terrain with varying features. For interpolation a modified version of Lowpass Gaussian filtering was implemented in order to blend biotope edges together. Asset distribution and road generation were implemented in a way that uses pseudo-randomness combined with heuristics. The user interface was done to tie everything together for testing. The results shows potential for assisting in procedural landscape creation with a large amount of freedom in customization. There is however flaws in some aspects, namely the interpolation methods suffer from clear visual artefacts. Whether it is suitable for professional standards remains to be fully proven objectively as the testing in this thesis work was limited.

In design matters, mechanisms with deformable elements are a step behind those with rigid bars, particularly if dimensional synthesis is considered a fundamental part of mechanism design. For the purposes of this work, a hybrid rigid–flexible four-bar mechanism has been chosen, the input bar being a continuum tendon of constant curvature. The coupler curves are noticeably more complex but offer more possibilities than the classical rigid four-bar counterpart. One of the objectives of this work is to completely characterize the coupler curves of this hybrid rigid–flexible mechanism, determining the number and type of circuits as well as constituent branches. Another important aim is to apply optimization techniques to the dimensional synthesis of path generation. Considerable progress in finding the best design solutions can be obtained if all the acquired knowledge about the coupler curves of this hybrid mechanism is integrated into the optimization algorithm.

The main goal of this research is to determine if an Inertial Navigation System (INS) can be corrected to effectively track a user’s pose, position and orientation, by using a monocular camera with fiducial markers. In addition, this research determines if an augmented reality (AR) system interface that integrates spatial cognition learning tasks can test and train the user’s spatial cognition. The implications of positive results are that the corrected INS poses on ubiquitous mobile devices provide reasonably accurate, precise, and reliable indoor navigation when a Global Navigation Satellite System (GNSS) is unavailable. This research investigates location-based services (LBS) for use in learning environments, tourism, and emergency services. The implementation technically enables the spatial cognition learning tasks. However, user tests results are still required to prove that user spatial cognition would improve and make navigating faster, which is a suggested area for future research., 2022-03

The main goal of this research is to determine if an Inertial Navigation System (INS) can be corrected to effectively track a user’s pose, position and orientation, by using a monocular camera with fiducial markers. In addition, this research determines if an augmented reality (AR) system interface that integrates spatial cognition learning tasks can test and train the user’s spatial cognition. The implications of positive results are that the corrected INS poses on ubiquitous mobile devices provide reasonably accurate, precise, and reliable indoor navigation when a Global Navigation Satellite System (GNSS) is unavailable. This research investigates location-based services (LBS) for use in learning environments, tourism, and emergency services. The implementation technically enables the spatial cognition learning tasks. However, user tests results are still required to prove that user spatial cognition would improve and make navigating faster, which is a suggested area for future research., 2022-03

The main goal of this research is to determine if an Inertial Navigation System (INS) can be corrected to effectively track a user’s pose, position and orientation, by using a monocular camera with fiducial markers. In addition, this research determines if an augmented reality (AR) system interface that integrates spatial cognition learning tasks can test and train the user’s spatial cognition. The implications of positive results are that the corrected INS poses on ubiquitous mobile devices provide reasonably accurate, precise, and reliable indoor navigation when a Global Navigation Satellite System (GNSS) is unavailable. This research investigates location-based services (LBS) for use in learning environments, tourism, and emergency services. The implementation technically enables the spatial cognition learning tasks. However, user tests results are still required to prove that user spatial cognition would improve and make navigating faster, which is a suggested area for future research., 2022-03, 2022-02-28T23:24:46Z

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.

We present an automated emergency trajectory generator to compute the best emergency trajectory for a given landing site. A combination of the optimized version of the rapidly exploring random tree algorithm and Dubins paths is used to compute a path connecting the aircraft position with the landing site, which avoids the obstacles in the way. Then, this path is used as input for a trajectory prediction (TP) algorithm, which computes a four-dimensional trajectory by taking into account the current aircraft performance and weather. The set of vertical profiles considered in the TP has been designed in order to cover the widest possible range of emergency situations. Moreover, the aircraft intents considered in these profiles are chosen by taking into account the operational requirements of the air traffic operation system and the input of the flight crew. Among these profiles, two have been tested during the study, to verify the result of the proposed algorithm and its computing time, which is one of the main success criteria. This concept is expected to be part of an advanced flight management system on-board function to help the pilot take efficient and effective decisions in emergency situations and adverse conditions., The work presented in this paper has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 864771, corresponding to the SafeNcy project (https://cordis.europa.eu/project/id/864771). The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union. The opinions expressed herein reflect the authors view only. Under no circumstances shall the Clean Sky 2 JU be responsible for any use that may be made of the information contained herein, Peer Reviewed, Postprint (published version)

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.

Co-production between scientific and Indigenous knowledge has been identified as useful to generating adaptation pathways with Indigenous peoples, who are attached to their traditional lands and thus highly exposed to the impacts of climate change. However, ignoring the complex and contested histories of nation-state colonisation can result in naïve adaptation plans that increase vulnerability. Here, through a case study in central Australia, we investigate the conditions under which co-production between scientific and Indigenous knowledge can support climate change adaptation pathways among place-attached Indigenous communities. A research team including scientists, Ltyentye Apurte Rangers and other staff from the Central Land Council first undertook activities to co-produce climate change presentations in the local Arrernte language; enable community members to identify potential adaptation actions; and implement one action, erosion control. Second, we reflected on the outcomes of these activities in order to unpack deeper influences. Applying the theory of articulation complexes, we show how ideologies, institutions and economies have linked Indigenous societies and the establishing Australian nation-state since colonisation. The sequence of complexes characterised as frontier, mission, pastoral, land-rights, community-development and re-centralisation, which is current, have both enabled and constrained adaptation options. We found knowledge co-production generates adaptation pathways when: (1) effective methods for knowledge co-production are used, based on deeply respectful partnerships, cultural governance and working together through five co-production tasks—prepare, communicate, discuss, bring together and apply; (2) Indigenous people have ongoing connection to their traditional territories to maintain their Indigenous knowledge; (3) the relationship between the Indigenous people and the nation-state empowers local decision-making and learning, which requi

Borescopes are a widely used technology for optically inspecting machinery from the inside. Recent solutions include enhanced metrology techniques for acquiring image data in high resolution as well as 3D surface information. These already foster more detailed health and damage inspections. However, both inspection and diagnosis strongly rely on the expertise of professionals. Despite their strong coupling, an increasing separation between these tasks is trending. Furthermore, many regions often cannot be inspected properly due to limitations in accessibility and hardware, which is particularly true within toroidal cavities. As a consequence, significant demands regarding emerging digitalization and automatization such as reproducibility, completeness or the steady and high quality of results cannot be fully satisfied. These drawbacks can be faced with a defined probe guidance while providing adjustability towards sensor characteristics. In this publication a novel approach with great automation capability is presented, facing the contactless and complete inspection of toroidal cavities, requiring no disassembly. The proposed solution is related to continuum robotics while based on tube forming technology coupled with a path planning strategy.

Borescopes are a widely used technology for optically inspecting machinery from the inside. Recent solutions include enhanced metrology techniques for acquiring image data in high resolution as well as 3D surface information. These already foster more detailed health and damage inspections. However, both inspection and diagnosis strongly rely on the expertise of professionals. Despite their strong coupling, an increasing separation between these tasks is trending. Furthermore, many regions often cannot be inspected properly due to limitations in accessibility and hardware, which is particularly true within toroidal cavities. As a consequence, significant demands regarding emerging digitalization and automatization such as reproducibility, completeness or the steady and high quality of results cannot be fully satisfied. These drawbacks can be faced with a defined probe guidance while providing adjustability towards sensor characteristics. In this publication a novel approach with great automation capability is presented, facing the contactless and complete inspection of toroidal cavities, requiring no disassembly. The proposed solution is related to continuum robotics while based on tube forming technology coupled with a path planning strategy.

This chapter reports on a life story of a hybrid organization, The Natural Step (TNS), that was founded in order to foster sustainability in society as a necessary philosophy for saving the planet. The organization was established as a hybrid that blended the logics of science, activism and consulting. Staying in this position was, however, not without challenge. The chapter contributes to discussions on management in hybrid organizations by highlighting when and why hybrids face particular challenges and how managers may struggle to deal with them. Over time, TNS gradually became de-hybridized into a management consultancy. The chapter concludes with a section on dilemmas faced by hybrid managers in cultivating and maintaining a hybrid identity over longer periods of time.

Automated vehicle control provides advantages in transport efficiency, redundancy, human-safety, flexibility, and parallelism. Extensive research has been dedicated to direct-following lateral control methods, using a single preview point as reference signal. However, these methods give rise to significant tracking errors. As alternative to a single point, a continuous path can be used as reference signal for vehicle control. Using a continuous reference path, accurate and comfortable control actions can be computed, while avoiding reference tracking errors. Therefore, robust reference path generation is an essential part of lateral vehicle control. The goal of this research is to develop a generic, robust reference path generator for lateral vehicle control. Currently in path generation, the state-of-the-art method is based on repetitive polynomial fitting. This method inherently contains two main weaknesses. Firstly, it is not robust to sensor noise and other real-world disturbances. Secondly, as a result of the repetitive fitting, a discontinuous path is generated. This is undesirable, because it leads to an unfeasible reference path, since vehicles can only produce and track continuous trajectories. Moreover, a discontinuous reference path results in the need for path smoothing when used in comfortable lateral vehicle control. Fundamentally, this smoothing leads to inaccurate control, caused by manipulation of the original, discontinuous reference path. To overcome these weaknesses, a new Model-based Path Generation method is presented. The development of a new, generic method for robust path generation is the main contribution of this research. This new path generation method is capable of producing feasible vehicle trajectories based on unfeasible waypoints. The performance of this method is evaluated in simulations and experiments, benchmarking it against polynomial fitting path generation. Furthermore, path generation robustness is assessed

Automated vehicle control provides advantages in transport efficiency, redundancy, human-safety, flexibility, and parallelism. Extensive research has been dedicated to direct-following lateral control methods, using a single preview point as reference signal. However, these methods give rise to significant tracking errors. As alternative to a single point, a continuous path can be used as reference signal for vehicle control. Using a continuous reference path, accurate and comfortable control actions can be computed, while avoiding reference tracking errors. Therefore, robust reference path generation is an essential part of lateral vehicle control. The goal of this research is to develop a generic, robust reference path generator for lateral vehicle control. Currently in path generation, the state-of-the-art method is based on repetitive polynomial fitting. This method inherently contains two main weaknesses. Firstly, it is not robust to sensor noise and other real-world disturbances. Secondly, as a result of the repetitive fitting, a discontinuous path is generated. This is undesirable, because it leads to an unfeasible reference path, since vehicles can only produce and track continuous trajectories. Moreover, a discontinuous reference path results in the need for path smoothing when used in comfortable lateral vehicle control. Fundamentally, this smoothing leads to inaccurate control, caused by manipulation of the original, discontinuous reference path. To overcome these weaknesses, a new Model-based Path Generation method is presented. The development of a new, generic method for robust path generation is the main contribution of this research. This new path generation method is capable of producing feasible vehicle trajectories based on unfeasible waypoints. The performance of this method is evaluated in simulations and experiments, benchmarking it against polynomial fitting path generation. Furthermore, path generation robustness is assessed

This paper investigates and conceptualises industry endogenous sources of innovation in a context of path dependency. With an embedded case study of the mature multi-technology lighting industry, it considers two cases of technology generation (fluorescent lamps and light-emitting diodes) that have occurred under the dominance of established incandescent technology. The results demonstrate the existence of common driving forces (variety of performance criteria and variety of lighting applications) behind the development of the existing path and the generation of two new paths. Such common driving forces indicate the existence of a reactive sequence or a logical causal relationship between the existing and the new paths, which serve as an enabling mechanism in endogenous path generation.

With the development of Unmanned Ground Vehicles (UGVs) in the last few decades, the demand for high accuracy in navigation is ever increasing. The four-wheel steering and four-wheel drive (4WS4WD) vehicle platform has great potential to solve existing problems, such as path following inaccuracy due to wheel slip and various forces generated on complex terrain. Although the configuration of 8 control inputs (i.e., 4 steering inputs and 4 drive inputs) can enhance the vehicle's maneuverability, it turns the vehicle into an over-actuated, highly coupled and nonlinear system, which poses a challenge for the control system design.This thesis makes contributions to three main areas related to the 4WS4WD vehicle. Firstly, a novel type of 4WS4WD vehicle incorporating force sensors is designed and manufactured for testing and experimentation. Accordingly, a kinematic model and a modular dynamic model composed of vehicle body dynamic model, driving unit dynamic model and tire model are developed to facilitate independent steering and force control at four individual wheels.Secondly, a new path generation method is proposed to smooth the rough reference paths that have sharp corners and discontinuous curvature. Using 7-order Bezier curves defined in the time domain, the modified path can also provide the smooth reference profiles of velocities and accelerations for the vehicle to follow. Note that the method proposed aims at smoothing predefined paths and providing motion profiles accordingly. The path planning problem is not in the scope of this research.Finally, two control methods are proposed for the 4WS4WD vehicle. A control method using Particle Swarm Optimization (PSO) is first presented to facilitate the independent force and steering control at individual wheels, which ensures the vehicle will follow the reference path as well as its motion profiles. Then, a control method integrating Sliding Mode Control (SMC) and PSO is presented combining the kinematic model based

This paper presents a geometry modelling approach to cross-section parameters of chamfered cutting edge on a ball-end mill of solid carbide (BEMSC). Both the cutting edge curve and the CR (chamfer in rake face) face models are derived. Based on the CR face model, a new method for CR face grinding path generation is proposed. By determining the relationship between the length and the angle parameters of the CR face equation, its grinding path can be derived. After solving the rake face equation using this method, its grinding path as well as the grinding paths of the LF (land on flank face) face and the second flank face can also be computed. The geometry model has been validated through a series of numerical simulations., QC 20151023

This dissertation presents the kinematic design of six-bar linkages for function, motion, and path generation by means of polynomial homotopy continuation algorithms. When no link dimensions are specified beforehand, the synthesis formulations for each design objective yield polynomial systems of degrees in the millions and billions, suggesting a large number of solutions. Complete solution sets to these systems have not yet been obtained and is the topic of this dissertation. Function generation for eleven positions is explored in most detail, in particular the Stephenson II and III function generators, for which we calculate multihomogeneous degrees of 264,241,152 and 55,050,240. A numerical reduction using homotopy estimates these systems to have 1,521,037 and 834,441 roots, respectively. For motion generation, the Watt I linkage can be specified for eight positions, producing a system of a multihomogeneous degree over 19 billion. However, for this work we focus on the smaller case of six positions, numerically reducing this system to an estimated 5,735 roots. For path generation we take a different approach. The design of path generators is formulated as RR chains constrained to have a single degree-of-freedom by attaching six-bar function generators to them. This enables us to use our results obtained on Stephenson II and III function generators to create four types of eleven position path generators: the Stephenson I linkage, two types of Stephenson II linkages, and the Stephenson III linkage.

This work deals with a new smooth path generation method for a mobile robot having a tricycle configuration. The method uses elementary and bi-elementary paths in order to create four kind of basic curves or paths. The proposed algorithm takes into account the real robot dimensions and can be applied for any initial and final orientation of the robot. The method generates a smooth path which is warranted to be very near of the original planning., En este trabajo se aborda un nuevo método de generación de caminos suaves y libres de obstáculos, para un robot con configuración triciclo, utilizando curvas elementales y bi-elementales. Mediante dichas curvas se crean cuatro tipos de curvas básicas o primitivas. Además al emplear las clotoides se utiliza una aproximación racional para la integral de Fresnel posibilitando una mayor rapidez en su resolución. El método que aquí se propone tiene en cuenta las dimensiones reales del robot y cualquier orientación inicial y final del mismo. Mediante el método propuesto se logra generar un camino suave y muy cercano al camino planificado.

This dissertation presents the kinematic design of six-bar linkages for function, motion, and path generation by means of polynomial homotopy continuation algorithms. When no link dimensions are specified beforehand, the synthesis formulations for each design objective yield polynomial systems of degrees in the millions and billions, suggesting a large number of solutions. Complete solution sets to these systems have not yet been obtained and is the topic of this dissertation. Function generation for eleven positions is explored in most detail, in particular the Stephenson II and III function generators, for which we calculate multihomogeneous degrees of 264,241,152 and 55,050,240. A numerical reduction using homotopy estimates these systems to have 1,521,037 and 834,441 roots, respectively. For motion generation, the Watt I linkage can be specified for eight positions, producing a system of a multihomogeneous degree over 19 billion. However, for this work we focus on the smaller case of six positions, numerically reducing this system to an estimated 5,735 roots. For path generation we take a different approach. The design of path generators is formulated as RR chains constrained to have a single degree-of-freedom by attaching six-bar function generators to them. This enables us to use our results obtained on Stephenson II and III function generators to create four types of eleven position path generators: the Stephenson I linkage, two types of Stephenson II linkages, and the Stephenson III linkage.

This work deals with a new smooth path generation method for a mobile robot having a tricycle configuration. The method uses elementary and bi-elementary paths in order to create four kind of basic curves or paths. The proposed algorithm takes into account the real robot dimensions and can be applied for any initial and final orientation of the robot. The method generates a smooth path which is warranted to be very near of the original planning., En este trabajo se aborda un nuevo método de generación de caminos suaves y libres de obstáculos, para un robot con configuración triciclo, utilizando curvas elementales y bi-elementales. Mediante dichas curvas se crean cuatro tipos de curvas básicas o primitivas. Además al emplear las clotoides se utiliza una aproximación racional para la integral de Fresnel posibilitando una mayor rapidez en su resolución. El método que aquí se propone tiene en cuenta las dimensiones reales del robot y cualquier orientación inicial y final del mismo. Mediante el método propuesto se logra generar un camino suave y muy cercano al camino planificado.

This paper presents a geometry modelling approach to cross-section parameters of chamfered cutting edge on a ball-end mill of solid carbide (BEMSC). Both the cutting edge curve and the CR (chamfer in rake face) face models are derived. Based on the CR face model, a new method for CR face grinding path generation is proposed. By determining the relationship between the length and the angle parameters of the CR face equation, its grinding path can be derived. After solving the rake face equation using this method, its grinding path as well as the grinding paths of the LF (land on flank face) face and the second flank face can also be computed. The geometry model has been validated through a series of numerical simulations., QC 20151113

This dissertation discusses vision-based static obstacle avoidance for a fleet of nonholonomic robots tasked to arrive at a final destination simultaneously. Path generation for each vehicle is computed using a single polynomial function that incorporates the vehicle constraints on velocity and acceleration and satisfies boundary conditions by construction. Furthermore, the arrival criterion and a preliminary obstacle avoidance scheme is incorporated into the path generation. Each robot is equipped with an inertial measurement unit that provides measurements of the vehicle's position and velocity, and a monocular camera that detects obstacles. The obstacle avoidance algorithm deforms the vehicle's original path around at most one obstacle per vehicle in a direction that minimizes an obstacle avoidance potential function. Deconfliction of the vehicles during obstacle avoidance is achieved by imposing a separation condition at the path generation level. Two estimation schemes are applied to estimate the unknown obstacle parameters. The first is an existing method known in the literature as Identifier-Based Observer and the second is a recently-developed fast estimator. It is shown that the performance of the fast estimator and its effect on the obstacle avoidance algorithm can be arbitrarily improved by the appropriate choice of parameters as compared to the Identifier-Based Observer method. Coordination in time of all vehicles is completed in an outer loop which adjusts the desired velocity profile of each vehicle in order to meet the simultaneous arrival constraints. Simulation results illustrate the theoretical findings.

The ability of mobile robots to generate feasible trajectories online is an important requirement for their autonomous operation in unstructured environments. Many path generation techniques focus on generation of time- or distance-optimal paths while obeying dynamic constraints, and often assume precise knowledge of robot and/or environmental (i.e. terrain) properties. In uneven terrain, it is essential that the robot mobility over the terrain be explicitly considered in the planning process. Further, since significant uncertainty is often associated with robot and/or terrain parameter knowledge, this should also be accounted for in a path generation algorithm. Here, extensions to the rapidly exploring random tree (RRT) algorithm are presented that explicitly consider robot mobility and robot parameter uncertainty based on the stochastic response surface method (SRSM). Simulation results suggest that the proposed approach can be used for generating safe paths on uncertain, uneven terrain. © 2009 IEEE.

This thesis studies path generation for industrial robots of six degrees of freedom. A path is defined by connection of simple geometrical objects like arcs and straight lines. About each point at which the objects connect, a region, henceforth called a zone, is defined in which deviation from the defined path is permitted. The zone allows the robot to follow the path at a constant speed, but the acceleration needed may vary. Some means of calculating the zone path as to make the acceleration continuous will be presented. In joint space the path is described by the use of cubic splines. The transformation of the Cartesian path to paths in joint space will be examined. Discontinuities in the second order derivatives will appear between the splines. A few examples of different zone path calculations will be presented where the resulting spline functions are compared with respect to their first and second order derivatives. An investigation of the number of spline functions needed when, given an upper limit of deviation, the transformation back to Cartesian coordinates is made.

This thesis studies path generation for industrial robots of six degrees of freedom. A path is defined by connection of simple geometrical objects like arcs and straight lines. About each point at which the objects connect, a region, henceforth called a zone, is defined in which deviation from the defined path is permitted. The zone allows the robot to follow the path at a constant speed, but the acceleration needed may vary. Some means of calculating the zone path as to make the acceleration continuous will be presented. In joint space the path is described by the use of cubic splines. The transformation of the Cartesian path to paths in joint space will be examined. Discontinuities in the second order derivatives will appear between the splines. A few examples of different zone path calculations will be presented where the resulting spline functions are compared with respect to their first and second order derivatives. An investigation of the number of spline functions needed when, given an upper limit of deviation, the transformation back to Cartesian coordinates is made.

Navy Mission Planner is a decision support tool for operational planning at the theater level. It takes as input a scenario defined by a list of ships and their (multi-mission) capabilities, a list of missions to be accomplished, their values to a commander, and their locations, and a fixed time horizon, and it produces as output an employment schedule consisting of a route plan and a set of missions to accomplish for each ship on each day in the scenario. It attempts to maximize the total value of missions covered in the scenario by utilizing each ship to the best of its capabilities, while balancing the geographic distribution of missions, the limited capability of the ships, and the limited time horizon. Prior versions used a limited enumeration routine to generate a manageable number of routes for each ship. We develop a heuristic route generator that reduces the runtime and provides better starting routes, improving the overall quality of solutions obtained by Navy Mission Planner., http://archive.org/details/heuristicroutege1094537690, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.