Paper
2 March 2001 Rover obstacle visualizer and navigability evaluator
Author Affiliations +
Proceedings Volume 4195, Mobile Robots XV and Telemanipulator and Telepresence Technologies VII; (2001) https://doi.org/10.1117/12.417300
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
The primary data used in ground-based, global path planning for NASA's Planetary Rovers are stereo images down-linked from the rover and range data derived from those images. The range data are often incomplete: the sensors are inherently noisy and sections of the landscape are blocked. This missing data complicates the path planning process and necessitates the help of human experts. We present the Rover Obstacle Visualizer and Navigability Evaluator (ROVANE), which assists these human experts and allows non-experts to plan missions without expert help. ROVANE generates a hazard map identifying slow, impassable, or dangerous regions with varying degrees of certainty. This map is used to create possible paths, which are assigned variable costs based on possible hazards. A hazard visualization is also produced, allowing the user to visually identify hazards and understand the system's path selection. As target locations are entered by the user, the system finds appropriate paths using a variation of the A* algorithm. A found path can be further modified by the user and output in a format suitable for commanding an actual rover. The system is capable of stand-alone operation, but is designed to be integrated into the Jet Propulsion Laboratory’s Web Interface for Telescience.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas G. Goodsell, Magnus Snorrason, Harald Ruda, and Vitaly Ablavsky "Rover obstacle visualizer and navigability evaluator", Proc. SPIE 4195, Mobile Robots XV and Telemanipulator and Telepresence Technologies VII, (2 March 2001); https://doi.org/10.1117/12.417300
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Visualization

Visibility

Cameras

Detection and tracking algorithms

Mars

Safety

Image analysis

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