Vision-based low-level navigation using a feed-forward neural network

• In this paper we propose a simple method for low-level navigation for autonomous mobile robots, employing an artificial neural network. Both corridor following and obstacle avoidance in indoor environments are managed by the same network. Raw grayscale images of size 32 x 23 pixels are processed one at a time by a feed-forward neural network. The output signals from the network directly control the motor control system of the robot. The feed-forward network is trained using the RPROP algorithm. Experiments in both familiar and unfamiliar environments are reported.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Engineering (hsv//eng)

Nyckelord

Robotics

Autonomous robots

Computer engineering

Datorteknik

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)