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• W3215740079 endingPage "127" @default.
• W3215740079 startingPage "127" @default.
• W3215740079 abstract "Robotics navigation and perception for forest management are challenging due to the existence of many obstacles to detect and avoid and the sharp illumination changes. Advanced perception systems are needed because they can enable the development of robotic and machinery solutions to accomplish a smarter, more precise, and sustainable forestry. This article presents a state-of-the-art review about unimodal and multimodal perception in forests, detailing the current developed work about perception using a single type of sensors (unimodal) and by combining data from different kinds of sensors (multimodal). This work also makes a comparison between existing perception datasets in the literature and presents a new multimodal dataset, composed by images and laser scanning data, as a contribution for this research field. Lastly, a critical analysis of the works collected is conducted by identifying strengths and research trends in this domain." @default.
• W3215740079 created "2021-12-06" @default.
• W3215740079 creator A5024946758 @default.
• W3215740079 creator A5038415360 @default.
• W3215740079 creator A5043134241 @default.
• W3215740079 creator A5063015996 @default.
• W3215740079 creator A5071982317 @default.
• W3215740079 date "2021-11-29" @default.
• W3215740079 modified "2023-10-05" @default.
• W3215740079 title "Unimodal and Multimodal Perception for Forest Management: Review and Dataset" @default.
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