Affiliation:
1. Computational Intelligence and Applications Research Group, Department of Computer Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK
2. Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal
3. Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal
Abstract
Artificial perception for robots operating in outdoor natural environments, including forest scenarios, has been the object of a substantial amount of research for decades. Regardless, this has proven to be one of the most difficult research areas in robotics and has yet to be robustly solved. This happens namely due to difficulties in dealing with environmental conditions (trees and relief, weather conditions, dust, smoke, etc.), the visual homogeneity of natural landscapes as opposed to the diversity of natural obstacles to be avoided, and the effect of vibrations or external forces such as wind, among other technical challenges. Consequently, we propose a new survey, describing the current state of the art in artificial perception and sensing for robots in precision forestry. Our goal is to provide a detailed literature review of the past few decades of active research in this field. With this review, we attempted to provide valuable insights into the current scientific outlook and identify necessary advancements in the area. We have found that the introduction of robotics in precision forestry imposes very significant scientific and technological problems in artificial sensing and perception, making this a particularly challenging field with an impact on economics, society, technology, and standards. Based on this analysis, we put forward a roadmap to address the outstanding challenges in its respective scientific and technological landscape, namely the lack of training data for perception models, open software frameworks, robust solutions for multi-robot teams, end-user involvement, use case scenarios, computational resource planning, management solutions to satisfy real-time operation constraints, and systematic field testing. We argue that following this roadmap will allow for robotics in precision forestry to fulfil its considerable potential.
Funder
Programa Operacional Regional do Centro, Portugal 2020, European Union FEDER
Fundação para a Ciência e Tecnologia
Subject
Artificial Intelligence,Control and Optimization,Mechanical Engineering
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