학술논문

WAVN: Wide Area Visual Navigation for Large-scale, GPS-denied Environments
Document Type
Conference
Source
2023 IEEE International Conference on Robotics and Automation (ICRA) Robotics and Automation (ICRA), 2023 IEEE International Conference on. :2039-2045 May, 2023
Subject
Robotics and Control Systems
Visualization
Automation
Navigation
Computational modeling
Surveillance
Merging
Semantics
Language
Abstract
This paper introduces a novel approach to GPS-denied visual navigation of a robot team over a wide (i.e., out of line of sight) area which we call WAVN (Wide Area Visual Navigation). Application domains include small-scale precision agriculture as well as exploration and surveillance. The proposed approach requires no exploration or map generation, merging, and updating, some of the most computationally intensive aspects of multi-robot navigation, especially in dynamic environments and for long-term deployments. In contrast, we extend the visual homing paradigm to leverage visual information from the entire team to allow a robot to home to a distant location. Since it only employs the latest imagery, the approach can be resilient to the current state of the environment. WAVN requires three components: identification of common landmarks between robots, a communication infrastructure, and an algorithm to find a sequence of common landmarks to navigate to a goal. The principal contribution of this paper is the navigation algorithm in addition to simulation and physical robot results characterizing performance. The approach is also compared to more traditional map-based approaches.