Autonomous Mobile Robots In Unknown Outdoor Environments
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Autonomous Mobile Robots in Unknown Outdoor Environments
Mobile robots have been increasingly applied in many different scenarios, such as space exploration and search and rescue, where the robots are required to travel over uneven terrain while outdoors. This book provides a new framework and the related algorithms for designing autonomous mobile robotic systems in such unknown outdoor environments.
Intelligent Autonomous Systems 9
Autonomy and adaptivity are key aspects of truly intelligent artificial systems, dating from the first IAS conference in 1989. The goal of IAS-9 is to lay out scientific ideas and design principles for artificial systems. This work contains papers that cover both the applied and the theoretical aspects of intelligent autonomous systems.
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment
This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.