This paper deals with a problem of autonomous mobile robot navigation among dynamic obstacles. The velocity obstacle approach (VO) is considered an easy and simple method to detect the collision situation between two circular-shaped objects using the collision cone principle. The VO approach has two challenges when applied in indoor environments. The first challenge is that in the real world, n...

Path planning contributes a very significant role in navigation of a mobile robot. The accuracy of path depends on mapping and localization of an indoor environment. A number of path planning approach are already in applications like A* Algorithms, D* Algorithm (Heuristic Approach), Dijkstra’s Algorithm (Deterministic approach), Cell Decomposition Technique etc. The conventional A* algorithm me...

A data acquisition software and hardware system was developed for acquiring geo-referenced shock and vibration data using National Instruments' LabView graphical programming language. This was used in conjunction with a modular data acquisition and signal conditioning system and a Differential Global Positioning System (DGPS) receiver. A prototype vehicle obstacle course, which introduced spati...

In this paper, we develop a vision based obstacle detection system by utilizing our proposed fisheye lens inverse perspective mapping (FLIPM) method. The new mapping equations are derived to transform the images captured by the fisheye lens camera into the undistorted remapped ones under practical circumstances. In the obstacle detection, we make use of the features of vertical edges on objects...

This paper presents a novel obstacle avoidance approach that is capable of dealing with both static and dynamic obstacles in the environment with guaranteed collision-free navigation for haptic teleoperation of VTOL aerial robots. The proposed approach modulates the set point for the vehicle’s controller based on the user input energy, estimated potential energy and vehicle’s kinetic energy. By...

Dynamic obstacle avoidance is an important, ubiquitous, and often challenging problem for autonomous mobile robots. This thesis presents a new method to guarantee collision avoidance with respect to moving obstacles that have constrained dynamics but move unpredictably. Velocity Obstacles have been widely used to plan trajectories that avoid collisions with obstacles under the assumption that t...

introduction. regarding the role of research in developing and improving a better culture, society and economics, 95% to 97% world finance in research belongs to developed countries while only 3%-5% to developing countries. although the universities as the major organizations are to do research works, it seems that there are some problems to bring this true. we tried to find out if a load of te...

A new reinforcement learning algorithm designed specifically for robots and embodied systems is described. Conventional reinforcement learning methods intended for learning general tasks suffer from a number of disadvantages in this domain including slow learning speed, an inability to generalise between states, reduced performance in dynamic environments, and a lack of scalability. Factor-Q, t...

A model of a topologically organized neural network of a Hopfield type with nonlinear analog neurons is shown to be very effective for path planning and obstacle avoidance. This deterministic system can rapidly provide a proper path, from any arbitrary start position to any target position, avoiding both static and moving obstacles of arbitrary shape. The model assumes that an (external) input ...