Abstract
This paper presents an alternative approach to implementing a stereo camera configuration for SLAM. The approach suggested implements a simplified method using a single RGB-D camera sensor mounted on a maneuverable non-holonomic mobile robot, the KCLBOT, used for extracting image feature depth information while maneuvering. Using a defined quadratic equation, based on the calibration of the camera, a depth computation model is derived base on the HSV color space map. Using this methodology it is possible to build navigation environment maps and carry out autonomous mobile robot path following and obstacle avoidance. This paper presents a calculation model which enables the distance estimation using the RGB-D sensor from Microsoft .NET micro framework device. Experimental results are presented to validate the distance estimation methodology.
Highlights
One of the fundamental problems in mobile robot autonomous navigation is map decomposition and building
Building maps as a mobile robot traverses a navigation environment, while using a partially composed map to maintain localization is better known as Simultaneous Localization and Mapping (SLAM)
The focus of the map building and localization methodology is for small form factor mobile robots using the Microsoft .NET Micro Framework [5], where the map building and localization methods are programmed using the limitations of the Windows Presentation Foundation (WPF) [6]
Summary
One of the fundamental problems in mobile robot autonomous navigation is map decomposition and building. The most common methods of building localization maps are using occupancy grids [2], feature building [3], and raw sensor telemetry [4]. In Leonard [3] et al.’s 1992 paper on feature building for dynamic maps for autonomous mobile robots, a critical point is made on sensor problems coming from noise and importance on the validation of sensor measurements. The approach presented by this paper uses a similar method, utilizing raw sensor telemetry via an inexpensive off the shelf RGB‐D camera. The focus of the map building and localization methodology is for small form factor mobile robots using the Microsoft .NET Micro Framework [5], where the map building and localization methods are programmed using the limitations of the Windows Presentation Foundation (WPF) [6]. The idea behind using a single RGD‐D camera is to simplify the stereo camera approach, and reduce the computation time to extract depth information from an image and use this image for SLAM
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