Deep Multi-Layer Perception Based Terrain Classification for Planetary Exploration Rovers
نویسندگان
چکیده
منابع مشابه
Multi-Sensor Terrain Estimation for Planetary Rovers
Future planetary exploration missions will require rovers to perform difficult tasks in rough terrain, with limited human supervision. Knowledge of terrain physical characteristics would allow a rover to adapt its control and planning strategies to maximize its effectiveness. This paper describes recent and current work at MIT in the area of terrain estimation and sensing. A method for on-line ...
متن کاملVision-based Terrain Classification and Classifier Fusion for Planetary Exploration Rovers
Autonomous rover operation plays a key role in planetary exploration missions. Rover systems require more and more autonomous capabilities to improve efficiency and robustness. Rover mobility is one of the critical components that can directly affect mission success. Knowledge of the physical properties of the terrain surrounding a planetary exploration rover can be used to allow a rover system...
متن کاملA study of visual and tactile terrain classification and classifier fusion for planetary exploration rovers
Knowledge of the physical properties of terrain surrounding a planetary exploration rover can be used to allow a rover system to fully exploit its mobility capabilities. Terrain classification methods provide semantic descriptions of the physical nature of a given terrain region. These descriptions can be associated with nominal numerical physical parameters, and/or nominal traversability estim...
متن کاملTerrain Adaptive Navigation for planetary rovers
This paper describes the design, implementation, and experimental results of a navigation system for planetary rovers called Terrain Adaptive Navigation (TANav). This system was designed to enable greater access to and more robust operations within terrains of widely varying slippage. The system achieves this goal by using onboard stereo cameras to remotely classify surrounding terrain, predict...
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ژورنال
عنوان ژورنال: Sensors
سال: 2019
ISSN: 1424-8220
DOI: 10.3390/s19143102