Stereo Vision-Based Optimal Path Planning with Stochastic Maps for Mobile Robot Navigation

  • Taimoor Shakeel Sheikh
  • Ilya M. Afanasyev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 867)


This paper addresses the problem of stereo vision-based environment mapping and optimal path planning for an autonomous mobile robot by using the methodology of getting 3D point cloud from disparity images, its transformation to 2D stochastic navigation map with occupancy grid cell values assigned from the set {obstacle, unoccupied, occupied}. We re-examined and extended this methodology with a combination of A-Star with binary heap algorithms for obstacle avoidance and indoor navigation of the Innopolis autonomous mobile robot with ZED stereo camera.


Stereo vision Optimal path planning Stochastic map Occupancy grid Disparity image Mobile robot navigation 



This work has been supported by the Russian Ministry of education and science with the project “Development of anthropomorphic robotic complexes with variable stiffness actuators for movement on the flat and the rugged terrains” (agreement: No14.606.21.0007, ID: RFMEFI60617X0007).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of RoboticsInnopolis UniversityInnopolisRussia

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