Akash Patel , Samuel Karlsson , Björn Lindqvist , Jakub Haluska , Christoforos Kanellakis , Ali Agha-mohammadi , George Nikolakopoulos
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引用次数: 0
Abstract
Exploration and safe navigation in previously unknown GPS-denied obstructed areas are major challenges for autonomous robots when deployed in subterranean environments. In response, this work establishes an Exploration-Planning framework developed for the real-world deployment of Micro Aerial Vehicles (MAVs) in subterranean exploration missions. The fundamental task for an autonomous MAV to navigate in an unknown area, is to decide where to look while navigating such that the MAV will acquire more information about the surrounding. The work presented in this article focuses around 3D exploration of large-scale caves or multi-branched tunnel like structures, while still prioritizing the Look-Ahead and Move-Forward approach for fast navigation in previously unknown areas. In order to achieve such exploration behaviour, the proposed work utilizes a two-layer navigation approach. The first layer deals with computing traversable frontiers to generate the look ahead poses in the constrained field of view, aligned with the MAV’s heading vector that leads to rapid continuous exploration. The proposed frontier distribution based switching goal selection approach allows the MAV to explore various terrains, while still regulating the MAV’s heading vector. The second layer of the proposed scheme deals with global cost based navigation of the MAV to the potential junction in a multi-branched tunnel system leading to a continuous exploration of partially seen areas. The proposed framework is a combination of a novel frontier goal selection approach, risk-aware expandable grid based path planning, nonlinear model predictive control and artificial potential fields based on local reactive navigation, obstacle avoidance, and control for the autonomous deployment of MAVs in extreme environments.
期刊介绍:
Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.
Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.