Real-time obstacle avoidance for polygonal robots with a reduced dynamic window (original) (raw)

Non holonomic shortest robot path planning in a dynamic environment using polygonal obstacles

2010

A collision free path planning method for the navigation of a circular mobile robot is presented. But this can be applied to a car-like robot, which has a restriction on minimum turning radius by making suitable assumptions. The navigation occurs in a dynamic environment with the presence of obstacles, modeled as polygon characterized by their offsets. We introduce a new methodology, for shortest robot path planning among polygonal obstacles in a dynamic environment using Mathematical Modeling with vector addition technique applied. The simulations presented show that the shortest path is generated and updated accordingly irrespective of number of obstacles encountered dynamically and that it considers the offset points of obstacles to automatically ensure perfect obstacle avoidance, regardless of the direction in which the robot is moving with less computation time.

Real-Time Obstacle-Avoiding Path Planning for Mobile Robots

AIAA Guidance, Navigation, and Control Conference, 2010

In this paper a computationally effective trajectory generation algorithm of mobile robots is proposed. The algorithm plans a reference path based on Voronoi diagram and Bézier curves, that meet obstacle avoidance criteria. Bézier curves defining the path are created such that the circumference convex polygon of their control points miss all obstacles. To give smoothness, they are connected under C 1 continuity constraint. In addition, the first Bézier curve is created to satisfy the initial heading constraint and to minimize the maximum curvature of the curve. For the mission, this paper analyzes the algebraic condition of control points of a quadratic Bézier curve to minimize the maximum curvature. The numerical simulations demonstrate smooth trajectory generation with satisfaction of obstacle avoidance in an unknown environment by applying the proposed algorithm in a receding horizon fashion.

Real-time obstacle avoidance of mobile robots

2007

This paper describes the formulation of the obstacle avoidance method to work in three-dimensional workspaces. We assume a spherical and omni-directional robot. The obstacle information is given in the form of points, which is the usual form in which sensor data is given. Obstacle avoidance methods are based on a real-time control process. Sensors collect information of the environment that is processed by the method to compute a motion command, the robot executes the motion and then the process restarts again. We show results that illustrate how this method successfully performs obstacle avoidance, and how it inherits the benefits of the original method being able to overcome the typical challenging problems of other obstacle avoidance methods but extrapolated to three dimensions.

Path Planning with Real Time Obstacle Avoidance

International Journal of Computer Applications, 2013

One of the most important areas of research on mobile robots is that of their moving from one point in a space to the other and that too keeping aloof from the different objects in their path i.e. real time obstacle detection. This is the basic problem of path planning through a continuous domain. For this a large number of algorithms have been proposed of which only a few are really good as far as local and global path planning are concerned as to some extent a trade of has to be made between the efficiency of the algorithm and its accuracy. In this project an integrated approach for both local as well as global path planning of a robot has been proposed. The primary algorithm that has been used for path planning is the artificial Potential field approach [1] and a* search algorithm has been used for finding the most optimum path for the robot. Obstacle detection for collision avoidance (a high level planning problem) can be effectively done by doing complex robot operations in real time and distributing the whole problem between different control levels. This project proposes the artificial potential field algorithm not only for static but also for moving obstacles using real time potential field values by creating sub-goals which eventually lead to the main goal of the most optimal complete path found by the A* search algorithm. Apart from these scan line and convex hull techniques have been used to improve the robustness of the algorithm. To some extent the shape and size of a robot has also been taken into consideration. The effectiveness of these algorithms has been verified with a series of simulations.

Real-Time Obstacle Avoidance for Manipulators and Mobile Robots

The International Journal of Robotics Research, 1986

This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to ...

Real-time Obstacle Avoidance for Fast Mobile Robots 12

1998

A new real-time obstacle avoidance approach for mobile robots has been developed and implemented. This approach permits the detection of unknown obstacles simultaneously with the steering of the mobile robot to avoid collisions and advancing toward the target. The novelty of this approach, entitled the Virtual Force Field, lies in the integration of two known concepts: Cer- tainty Grids for

Real-time obstacle avoidance for fast mobile robots

1989

The method described, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. A VFH-controlled mobile robot maneuvers quickly and without stopping among densely cluttered obstacles. The VFH method uses a two-dimensional Cartesian histogram grid as a world model. This world model is updated continuously and

Obstacle avoidance for a mobile robot

Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications, 1989

The basic problem in obstacle avoidance is the cooperation between the sensor system and the trajectory control system. Normally, the trajectory control receives a path specification from the global path planning algorithm. Based on complete knowledge of the environment, this algorithm is able to compute a detailed path. However, as soon as an unknown object is detected on the path, the robot must rely on its sensors to guide it along the contour of the objrct. A t the samr time information about the object is acquired, which can be put in the world model. The sensor system must specify a local path for the robot. In this paper an obstacle avoidance strategy for a mobile robot is discussed, which is based on the use of ultrasonic sensors. Only static obstacles with right angles are assumed, though the obstacles may be non-convex. The path of the robot is specified by means of line segments and waypoints at the intersections of these lines. The contour of the obstacle is also described by lines. In this way path following and obstacle avoidance have been integrated in one trajectory control routine. The avoidance algorithm is described and attention is paid to the interpretation of the data from the ultrasonic sensors.

Real-Time Robot Path Planning via a Distance-Propagating Dynamic System with Obstacle Clearance

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2000

An efficient grid-based distance-propagating dynamic system is proposed for real-time robot path planning in dynamic environments, which incorporates safety margins around obstacles using local penalty functions. The path through which the robot travels minimizes the sum of the current known distance to a target and the cumulative local penalty functions along the path. The algorithm is similar to D* but does not maintain a sorted queue of points to update. The resulting gain in computational speed is offset by the need to update all points in turn. Consequently, in situations where many obstacles and targets are moving at substantial distances from the current robot location, this algorithm is more efficient than D*. The properties of the algorithm are demonstrated through a number of simulations. A sufficient condition for capture of a target is provided.