A Robot Navigation Algorithm for Moving Obstacles

In recent years, considerable progress has been made towards the development of intelligent autonomous mobile robots which can perform a wide variety of tasks. Although the capabilities of these robots vary significantly, each must have the ability to navigate within its environment from a starting location to a goal without experiencing collisions with obstacles in the process - a capability commonly referred to as robot navigation . Numerous algorithms for robot navigation have been developed which allow the robot to operate in static environments. However, little work has been accomplished in the development of algorithms which allow the robot to navigate in a dynamic environment. This thesis presents a mathematically-based navigation algorithm for a robot operating in a continuous-time environment inhabited by moving obstacles whose trajectories and velocities can be detected. In this methodology, the obstacles are represented as sheared cylinders to depict the areas swept out by the obstacle disks of influence over time. The robot is represented by the cone of positions it can reach by traveling at a constant speed in any direction. The methodology utilizes a three-dimensional navigation planning approach in which the search points, or tangent points, are the points in time at which the robot tangentially meets the obstacles. These tangent points are determined by calculating the intersection curves between the robot and the obstacles, and then using the first derivative of the intersection curves to make the tangent selections. Paths are created as sequences of these tangent points leading from the robot starting location to the goal, and are searched using the A* strategy, with a heuristic of the Euclidean distance from the tangent point to the goal. The main contribution of this thesis is the development of a methodology which produces optimal tangent paths to the goal for a dynamic robot environment. This feature is significant, since no other algorithm located in the literature survey as background to this thesis has shown the ability to produce paths with optimal properties

A study of mobile robot motion planning

This thesis studies motion planning for mobile robots in various environments. The basic tools for the research are the configuration space and the visibility graph. A new approach is developed which generates a smoothed minimum time path. The difference between this and the Minimum Time Path at Visibility Node (MTPVN) is that there is more clearance between the robot and the obstacles, and so it is safer. The accessibility graph plays an important role in motion planning for a massless mobile robot in dynamic environments. It can generate a minimum time motion in 0(n2»log(n)) computation time, where n is the number of vertices of all the polygonal obstacles. If the robot is not considered to be massless (that is, it requires time to accelerate), the space time approach becomes a 3D problem which requires exponential time and memory. A new approach is presented here based on the improved accessibility polygon and improved accessibility graph, which generates a minimum time motion for a mobile robot with mass in O((n+k)2»log(n+k)) time, where n is the number of vertices of the obstacles and k is the number of obstacles. Since k is much less than n, so the computation time for this approach is almost the same as the accessibility graph approach. The accessibility graph approach is extended to solve motion planning for robots in three dimensional environments. The three dimensional accessibility graph is constructed based on the concept of the accessibility polyhedron. Based on the properties of minimum time motion, an approach is proposed to search the three dimensional accessibility graph to generate the minimum time motion. Motion planning in binary image representation environment is also studied. Fuzzy logic based digital image processing has been studied. The concept of Fuzzy Principal Index Of Area Coverage (PIOAC) is proposed to recognise and match objects in consecutive images. Experiments show that PIOAC is useful in recognising objects. The visibility graph of a binary image representation environment is very inefficient, so the approach usually used to plan the motion for such an environment is the quadtree approach. In this research, polygonizing an obstacle is proposed. The approaches developed for various environments can be used to solve the motion planning problem without any modification. A simulation system is designed to simulate the approaches

Invariance and control of autonomous vehicles

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Universidade do Porto. Faculdade de Engenharia. 201

Most vital segment barriers

We study continuous analogues of "vitality" for discrete network flows/paths, and consider problems related to placing segment barriers that have highest impact on a flow/path in a polygonal domain. This extends the graph-theoretic notion of "most vital arcs" for flows/paths to geometric environments. We give hardness results and efficient algorithms for various versions of the problem, (almost) completely separating hard and polynomially-solvable cases