Abstract
For an autonomous mobile robot operating in an unknown environment, distinguishing obstacles from the traversable ground region is an essential step in determining whether the robot can traverse th...
Highlights
Autonomous mobile robots are intelligent machines that are capable of acting on their own, sensing their surrounding environment, and independently performing tasks without explicit human control
We describe the mean height evaluation technique, which is included in our final algorithm and is discussed in “Ground segmentation method based on the gradient field” section
To more explicitly present our evaluation of the proposed ground segmentation method compared to the naıve gradient field approach, we provide screenshots of our experiments with two types of ground data
Summary
Autonomous mobile robots are intelligent machines that are capable of acting on their own, sensing their surrounding environment, and independently performing tasks without explicit human control. An important objective of automation robotics research is to enable the robot to perceive and interpret terrain for safe movement and the ability to collect data, handle its processing, and compute in real time. To this end, a traditional approach is to use a digital camera for two-dimensional (2D) machine vision to capture images of objects, perform image preprocessing, and execute computer vision techniques to extract useful information. The increased availability of new solutions has made these technologies more robust and easier to use, while opening new capabilities and presenting interesting challenges for 3D machine vision.
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