Found 13 results
Article
26 January 2024A Lightweight Visual Navigation and Control Approach to the 2022 RoboMaster Intelligent UAV Championship
In this paper, an autonomous system is developed for drone racing. On account of their vast consumption of computing resources, the methods for visual navigation commonly employed are discarded, such as visual-inertial odometry (VIO) or simultaneous localization and mapping (SLAM). A series of navigation algorithms for autonomous drone racing, which can operate without the aid of the information on the external position, are proposed: one for lightweight gate detection, achieving gates detection with a frequency of 60 Hz; one for direct collision detection, seeking the maximum passability in-depth images. Besides, a velocity planner is adopted to generate velocity commands according to the results from visual navigation, which are enabled to perform a guidance role when the drone is approaching and passing through gates, assisting it in avoiding obstacles and searching for temporarily invisible gates. The approach proposed above has been demonstrated to successfully help our drone passing-through complex environments with a maximum speed of 2.5 m/s and ranked first at the 2022 RoboMaster Intelligent UAV Championship.
Review
08 November 2023Review on Drone-Assisted Air-Quality Monitoring Systems
Drone-aided systems have gained popularity in the last few decades due to their stability in various commercial sectors and military applications. The conventional ambient air quality monitoring stations (AAQMS) are immovable and big. This drawback has been significantly overcome by drone-aided low-cost sensor (LCS) modules. As a result, much research work, media information, and technical notes have been released on drone-aided air quality and ecological monitoring and mapping applications. This work is a sincere effort to provide a comprehensive and structured review of commercial drone applications for air quality and environmental monitoring. The collected scientific and non-scientific information was divided according to the different drone models, sensor types, and payload weights. The payload component is very critical in stablility of the multirotor drones. Most study projects installed inexpensive sensors on drones according to the avilibility of the space on drone frame. After reviewing of multiple environmental applications the common payload range was 0 gm to 4000 gm. The crucial elements are addressed, including their relation to meteorological factors, air isokinetics, propeller-induced downwash, sensor mounting location, ramifications etc. As a result, technical recommendations for AQ monitoring assisted by drones are addressed in the debate part. This work will help researchers and environmentalists choose sensor-specific payloads for drones and mounting locations. Also, it enables advanced methods of monitoring parameters that help policymakers to frame advanced protocols and sensor databases for the environment and ecology.
