VFH/sup */: local obstacle avoidance with look-ahead verification

By Iwan Ulrich, Johann Borenstein. Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), 2000

484 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/60f389d8def6c93aab17faf369f0727edbd51f47

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Citations in the corpus

Safe motion planning in dynamic environments (2005, background): “The trajectory to be followed, ie this discrete sequence of velocities, is determined by mean of a navigation function [16] or an incremental algorithm that builds a tree within the velocity space [17], [18], [19].”
Design and use paradigms for Gazebo, an open-source multi-robot simulator (2004, methodology): “For example, it is possible to use Player’s VFH (Vector Field Histogram) [ 10 ] or AMCL (Adaptive Monte-Carlo Localization) [11] interchangeably between real and simulated environments.”
Offline and Online Search: UAV Multiobjective Path Planning Under Dynamic Urban Environment (2018, methodology): “Typical geometry methods include the potential field method [5], the vector field histogram method [6], and the Voronoi diagram method [7].”
Introduction to Autonomous Mobile Robots (2004, methodology): “Later, Borenstein, together with Ulrich, extended the VFH algorithm to yield VFH+ [150] and VFH*[149].”
The GuideCane-applying mobile robot technologies to assist the visually impaired (2001, methodology): “During the GuideCane development, the original VFH method was successively improved, resulting in the VFH+ and VFH* algorithms [16; 17 ].”