mobile robot online motion planning using generalized voronoi graphs

نویسندگان

elips masehian

amin naseri

چکیده

in this paper, a new online robot motion planner is developed for systematically exploring unknown environâ¬ments by intelligent mobile robots in real-time applications. the algorithm takes advantage of sensory data to find an obstacle-free start-to-goal path. it does so by online calculation of the generalized voronoi graph (gvg) of the free space, and utilizing a combination of depth-first and breadth-first searches on the gvg. the planner is equipped with components such as step generation and correction, backtracking, and loop handling. it is fast, simple, complete, and extendable to higher spaces.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Mobile Robot Online Motion Planning Using Generalized Voronoi Graphs

In this paper, a new online robot motion planner is developed for systematically exploring unknown environ¬ments by intelligent mobile robots in real-time applications. The algorithm takes advantage of sensory data to find an obstacle-free start-to-goal path. It does so by online calculation of the Generalized Voronoi Graph (GVG) of the free space, and utilizing a combination of depth-first an...

متن کامل

Mobile Robot Online Motion Planning Using Generalized Voronoi Graphs

In this paper, a new online robot motion planner is developed for systematically exploring unknown environments by intelligent mobile robots in real-time applications. The algorithm takes advantage of sensory data to find an obstacle-free start-to-goal path. It does so by online calculation of the Generalized Voronoi Graph (GVG) of the free space, and utilizing a combination of depth-first and ...

متن کامل

Robot Motion Planning Using Generalised Voronoi Diagrams

In robot motion planning in a space with obstacles, the goal is to find a collision-free path of robot from the starting to the target position. There are many fundamentally different approaches, and their modifications, to the solution of this problem depending on types of obstacles, dimensionality of the space and restrictions for robot movements. Among the most frequently used are roadmap me...

متن کامل

Interactive Motion Planning Using Hardware - AcceleratedComputation of Generalized Voronoi

We present techniques for fast motion planning by using discrete approximations of generalized Voronoi diagrams, computed with graphics hardware. Approaches based on this diagram computation are applicable to both static and dynamic environments of fairly high complexity. We compute a discrete Voronoi diagram by rendering a three-dimensional distance mesh for each Voronoi site. The sites can be...

متن کامل

Kinodynamic Robot Motion Planning Based on the Generalised Voronoi Diagram

Kinodynamic motion planning of an autonomous robot in an unknown or partially known indoor or outdoor environment is a challenging task, especially when the generated path must maintain the largest distance from surrounding obstacles and the robot’s kinodynamic properties, its localisation, and uncertainty of the environment are also considered. A new motion planning technique, which is built o...

متن کامل

Sensor Based Motion Planning : The Hierarchical Generalized Voronoi Graph

The hierarchical generalized Voronoi graph (HGVG) is a roadmap that can serve as a basis for sensor based robot motion planning. A key feature of the HGVG is its incremental construction procedure that uses only line of sight distance information. This work describes basic properties of the HGVG and the procedure for its incremental construction using local range sensors. Simulations and experi...

متن کامل

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید


عنوان ژورنال:
journal of optimization in industrial engineering

ناشر: qiau

ISSN 2251-9904

دوره Volume 3

شماره Issue 5 2010

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023