Path Planning Based on Fuzzy Decision Trees and Potential Field

The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path

DAQL-Enabled Autonomous Vehicle Navigation in Dynamically Changing Environment

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Collision-free path planning for robots using B-splines and simulated annealing

This thesis describes a technique to obtain an optimal collision-free path for an automated guided vehicle (AGV) and/or robot in two and three dimensions by synthesizing a B-spline curve under geometric and intrinsic constraints. The problem is formulated as a combinatorial optimization problem and solved by using simulated annealing. A two-link planar manipulator is included to show that the B-spline curve can also be synthesized by adding kinematic characteristics of the robot. A cost function, which includes obstacle proximity, excessive arc length, uneven parametric distribution and, possibly, link proximity costs, is developed for the simulated annealing algorithm. Three possible cases for the orientation of the moving object are explored: (a) fixed orientation, (b) orientation as another independent variable, and (c) orientation given by the slope of the curve. To demonstrate the robustness of the technique, several examples are presented. Objects are modeled as ellipsoid type shapes. The procedure to obtain the describing parameters of the ellipsoid is also presented

Secured force guidance of an omnidirectional non-holonomic platform

For robots to operate in real life settings, they must be able to physically interact with the environment, and for instance be able to react to force-guidance interactions. However, only a few research projects have addressed such capabilities, developing prototypes that have to be pushed from their handle bars. AZIMUT-3 is a novel omnidirectional non-holonomic mobile robot developed at IntRoLab (Intelligent, Interactive and Interdisciplinary Robot Lab, Université de Sherbrooke) with force-controlled active steering. This results in a horizontal suspension effect for which the mechanical impedance of the steering actuators can be controlled. This makes the platform ideal for developing physical guidance algorithms. One such algorithm is secured shared-control, making the platform go in the direction of the user pushing the robot while still making it move safely by avoiding obstacles. Such capability is somewhat novel in the field, and the objective is to provide safe navigation with maximum control to the user. This Master's thesis has two important contributions: an algorithm to estimate the applied efforts on AZIMUT-3 from torque measurements on its wheels; an algorithm to use these efforts with obstacle detection using laser range finder data to implement a safe, shared-control approach. Experimental results using the real platform demonstrate feasibility and safe control of the system, with performances similar to using a six degrees of freedom force sensor but at lower cost and with a broader area for shared control. Our implementation also resulted in coupling the simulation environment Webots with the ROS (Robot Operating System) library from Willow Garage, to help develop our approach in simulation before using AZIMUT-3. Overall, our work is the first in demonstrating how it is possible to naturally interact by physically moving or positioning a mobile platform in real life settings, a capability which could be useful for instance in the design of powered shopping carts or active walkers

MS

thesisIn this research, a computerized motion planning and control system for multiple robots is presented. Medium scale wheeled mobile robot couriers move wireless antennas within a semicontrolled environment. The systems described in this work are integrated as components within Mobile Emulab, a wireless research testbed. This testbed is publicly available to users remotely via the Internet. Experimenters use a computer interface to specify desired paths and configurations for multiple robots. The robot control and coordination system autonomously creates complex movements and behaviors from high level instructions. Multiple trajectory types may be created by Mobile Emulab. Baseline paths are comprised of line segments connecting waypoints, which require robots to stop and pivot between each segment. Filleted circular arcs between line segments allow constant motion trajectories. To avoid curvature discontinuities inherent in line-arc segmented paths, higher order continuous polynomial spirals and splines are constructed in place of the constant radius arcs. Polar form nonlinear state feedback controllers executing on a computer system connected to the robots over a wireless network accomplish posture stabilization, path following and trajectory tracking control. State feedback is provided by an overhead camera based visual localization system integrated into the testbed. Kinematic control is used to generate velocity commands sent to wheel velocity servo loop controllers built into the robots. Obstacle avoidance in Mobile Emulab is accomplished through visibility graph methods. The Virtualized Phase Portrait Method is presented as an alternative. A virtual velocity field overlay is created from workspace obstacle zone data. Global stability to a single equilibrium point, with local instability in proximity to obstacle regions is designed into this system

Методы планирования пути в среде с препятствиями (обзор)

Planning the path is the most important task in the mobile robot navigation. This task involves basically three aspects. First, the planned path must run from a given starting point to a given endpoint. Secondly, it should ensure robot’s collision-free movement. Thirdly, among all the possible paths that meet the first two requirements it must be, in a certain sense, optimal.Methods of path planning can be classified according to different characteristics. In the context of using intelligent technologies, they can be divided into traditional methods and heuristic ones. By the nature of the environment, it is possible to divide planning methods into planning methods in a static environment and in a dynamic one (it should be noted, however, that a static environment is rare). Methods can also be divided according to the completeness of information about the environment, namely methods with complete information (in this case the issue is a global path planning) and methods with incomplete information (usually, this refers to the situational awareness in the immediate vicinity of the robot, in this case it is a local path planning). Note that incomplete information about the environment can be a consequence of the changing environment, i.e. in a dynamic environment, there is, usually, a local path planning.Literature offers a great deal of methods for path planning where various heuristic techniques are used, which, as a rule, result from the denotative meaning of the problem being solved. This review discusses the main approaches to the problem solution. Here we can distinguish five classes of basic methods: graph-based methods, methods based on cell decomposition, use of potential fields, optimization methods, фтв methods based on intelligent technologies.Many methods of path planning, as a result, give a chain of reference points (waypoints) connecting the beginning and end of the path. This should be seen as an intermediate result. The problem to route the reference points along the constructed chain arises. It is called the task of smoothing the path, and the review addresses this problem as well.Планирование пути — важнейшая задача в области навигации мобильных роботов. Эта задача включает в основном три аспекта. Во-первых, спланированный путь должен пролегать от заданной начальной точки к заданной конечной точке. Во-вторых, этот путь должен обеспечивать движение робота с обходом возможных препятствий. В-третьих, путь должен среди всех возможных путей, удовлетворяющих первым двум требованиям, быть в определенном смысле оптимальным.Методы планирования пути можно классифицировать по разным признакам. В контексте использования интеллектуальных технологий их можно разделить на традиционные методы и эвристические методы. По характеру окружающей обстановки можно разделить методы планирования на методы планирования в статической окружающей среде и в динамической среде (следует, однако, отметить, что статическая окружающая среда редко встречается на практике). Методы также можно разделить по полноте информации об окружающей среде: методы с полной информацией (в таком случае говорят о глобальном планировании пути) и методы с неполной информацией (обычно речь идет о знании обстановки в непосредственной близости от робота, в этом случае речь идет о локальном планировании пути). Отметим, что неполная информация об окружающей среде может быть следствием меняющейся обстановки, т.е. в условиях динамической среды планирование пути, как правило, локальное.В литературе предложено большое количество методов планирования пути, в которых используются различные эвристические приемы, вытекающие, как правило, из содержательного смысла решаемой задачи. В настоящем обзоре  рассматриваются основные подходы к решению задачи. Здесь можно выделить пять классов основных методов: методы на основе графов, методы на основе клеточной декомпозиции, использование потенциальных полей, оптими­зационные методы, методы на основе интеллектуальных технологий.Многие методы планирования пути в качестве результата дают цепь опорных точек (путевых точек), соединяющую начало и конец пути. Это следует рассматривать как промежуточный результат. Возникает задача прокладки пути вдоль построенной цепи опорных точек, называемая задачей сглаживания пути. Этой задаче в обзоре также уделено внимание

An Original Approach for a Better Remote Control of an Assistive Robot

Many researches have been done in the field of assistive robotics in the last few years. The first application field was helping with the disabled people\\u27s assistance. Different works have been performed on robotic arms in three kinds of situations. In the first case, static arm, the arm was principally dedicated to office tasks like telephone, fax... Several autonomous modes exist which need to know the precise position of objects. In the second configuration, the arm is mounted on a wheelchair. It follows the person who can employ it in more use cases. But if the person must stay in her/his bed, the arm is no more useful. In a third configuration, the arm is mounted on a separate platform. This configuration allows the largest number of use cases but also poses more difficulties for piloting the robot. The second application field of assistive robotics deals with the assistance at home of people losing their autonomy, for example a person with cognitive impairment. In this case, the assistance deals with two main points: security and cognitive stimulation. In order to ensure the safety of the person at home, different kinds of sensors can be used to detect alarming situations (falls, low cardiac pulse rate...). For assisting a distant operator in alarm detection, the idea is to give him the possibility to have complementary information from a mobile robot about the person\\u27s activity at home and to be in contact with the person. Cognitive stimulation is one of the therapeutic means used to maintain as long as possible the maximum of the cognitive capacities of the person. In this case, the robot can be used to bring to the person cognitive stimulation exercises and stimulate the person to perform them. To perform these tasks, it is very difficult to have a totally autonomous robot. In the case of disabled people assistance, it is even not the will of the persons who want to act by themselves. The idea is to develop a semi-autonomous robot that a remote operator can manually pilot with some driving assistances. This is a realistic and somehow desired solution. To achieve that, several scientific problems have to be studied. The first one is human-machine-cooperation. How a remote human operator can control a robot to perform a desired task? One of the key points is to permit the user to understand clearly the way the robot works. Our original approach is to analyse this understanding through appropriation concept introduced by Piaget in 1936. As the robot must have capacities of perceptio

Integration of fault tolerance and hardware redundancy techniques into the design of mobile platforms

This work addresses the development of a fault-tolerant mobile platform. Fault-tolerant mechanical system design is an emerging technology that attempts to build highly reliable systems by incorporating hardware and software architectures. For this purpose, previous work in fault-tolerant were reviewed. Alternate architectures were evaluated to maximize the fault tolerance capabilities of the driving and steering systems of a mobile platform. The literature review showed that most of the research work on fault tolerance has been done in the area of kinematics and control systems of robotic arms. Therefore, hardware redundancy and fault tolerance in mobile robots is an area to be researched. The prototype constructed as part of this work demonstrated basic principles and uses of a fault-tolerant mechanism, and is believed to be the first such system in its class. It is recommended that different driving and steering architectures, and the fault-tolerant controllers\u27 performance be tested on this prototype

INTELLIGENT VISION-BASED NAVIGATION SYSTEM

This thesis presents a complete vision-based navigation system that can plan and follow an obstacle-avoiding path to a desired destination on the basis of an internal map updated with information gathered from its visual sensor. For vision-based self-localization, the system uses new floor-edges-specific filters for detecting floor edges and their pose, a new algorithm for determining the orientation of the robot, and a new procedure for selecting the initial positions in the self-localization procedure. Self-localization is based on matching visually detected features with those stored in a prior map. For planning, the system demonstrates for the first time a real-world application of the neural-resistive grid method to robot navigation. The neural-resistive grid is modified with a new connectivity scheme that allows the representation of the collision-free space of a robot with finite dimensions via divergent connections between the spatial memory layer and the neuro-resistive grid layer. A new control system is proposed. It uses a Smith Predictor architecture that has been modified for navigation applications and for intermittent delayed feedback typical of artificial vision. A receding horizon control strategy is implemented using Normalised Radial Basis Function nets as path encoders, to ensure continuous motion during the delay between measurements. The system is tested in a simplified environment where an obstacle placed anywhere is detected visually and is integrated in the path planning process. The results show the validity of the control concept and the crucial importance of a robust vision-based self-localization process

Hybrid approaches for mobile robot navigation

The work described in this thesis contributes to the efficient solution of mobile robot navigation problems. A series of new evolutionary approaches is presented. Two novel evolutionary planners have been developed that reduce the computational overhead in generating plans of mobile robot movements. In comparison with the best-performing evolutionary scheme reported in the literature, the first of the planners significantly reduces the plan calculation time in static environments. The second planner was able to generate avoidance strategies in response to unexpected events arising from the presence of moving obstacles. To overcome limitations in responsiveness and the unrealistic assumptions regarding a priori knowledge that are inherent in planner-based and a vigation systems, subsequent work concentrated on hybrid approaches. These included a reactive component to identify rapidly and autonomously environmental features that were represented by a small number of critical waypoints. Not only is memory usage dramatically reduced by such a simplified representation, but also the calculation time to determine new plans is significantly reduced. Further significant enhancements of this work were firstly, dynamic avoidance to limit the likelihood of potential collisions with moving obstacles and secondly, exploration to identify statistically the dynamic characteristics of the environment. Finally, by retaining more extensive environmental knowledge gained during previous navigation activities, the capability of the hybrid navigation system was enhanced to allow planning to be performed for any start point and goal point