LiDAR-based Quadrotor for Slope Inspection in Dense Vegetation
University of Hong Kong（香港大学）；Geotechnical Engineering Office（土力工程处）；Civil and Engineering Development Department（土木工程拓展署）；The Government of Hong Kong SAR（香港特别行政区政府）
Wenyi Liu, Yunfan Ren, Rui Guo, Vickie W. W. Kong, Anthony S. P. Hung, Fangcheng Zhu, Yixi Cai, Yuying Zou, Fu Zhang
This work presents a LiDAR-based quadrotor system for slope inspection in dense vegetation environments. Cities like Hong Kong are vulnerable to climate hazards, which often result in landslides. To mitigate the landslide risks, the Civil Engineering and Development Department (CEDD) has constructed steel flexible debris-resisting barriers on vulnerable natural catchments to protect residents. However, it is necessary to carry out regular inspections to identify any anomalies, which may affect the proper functioning of the barriers. Traditional manual inspection methods face challenges and high costs due to steep terrain and dense vegetation. Compared to manual inspection, unmanned aerial vehicles (UAVs) equipped with LiDAR sensors and cameras have advantages such as maneuverability in complex terrain, and access to narrow areas and high spots. However, conducting slope inspections using UAVs in dense vegetation poses significant challenges. First, in terms of hardware, the overall design of the UAV must carefully consider its maneuverability in narrow spaces, flight time, and the types of onboard sensors required for effective inspection. Second, regarding software, navigation algorithms need to be designed to enable obstacle avoidance flight in dense vegetation environments. To overcome these challenges, we develop a LiDAR-based quadrotor, accompanied by a comprehensive software system. The goal is to deploy our quadrotor in field environments to achieve efficient slope inspection. To assess the feasibility of our hardware and software system, we conduct functional tests in non-operational scenarios. Subsequently, invited by CEDD, we deploy our quadrotor in six field environments, including five flexible debris-resisting barriers located in dense vegetation and one slope that experienced a landslide. These experiments demonstrated the superiority of our quadrotor in slope inspection.
Spiral Trajectories for Building Inspection with Quadrotors
Centro de Innovación y Desarrollo Tecnológico en Cómputo (CIDETEC), Instituto Politécnico Nacional (IPN)（国家理工学院（IPN）计算技术创新与发展中心（CIDETEC））；Universidad de Quintana Roo（金塔纳罗奥大学）；Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional (IPN)（国家理工学院（IPN）计算研究中心（CIC））
Aerial Inspection Behaviors via RL-based Quadrotor Control for Under-canopy Forest Environments
Robotics and AI group, in the Department of Computer Science, Electrical and Space Engineering at Luleå University of Technology, Sweden（鲁尔坎大学技术学院机器人与人工智能小组，计算机科学、电气与空间工程系，瑞典）
Autonomous UAV Pipeline Near-proximity Inspection via Disturbance-Aware Predictive Visual Servoing
School of Automation, Key Laboratory of Measurement and Control of CSE, Ministry of Education, Southeast University（自动化学院、CSE测量与控制重点实验室、教育部、东南大学）；Department of Aeronautical and Automotive Engineering, Loughborough University（航空与汽车工程系、罗汉布大学）；Research Centre for Low Altitude Economy and the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University（低空经济研究中心和航空与航空工程系、香港理工大学）
A Heuristic Approach for Performance Tuning in RL-based Quadrotor Control via Reward Design and Termination Conditions
Robotics and AI group, in the Department of Computer Science, Electrical and Space Engineering at Luleå University of Technology（鲁德尼大学机器人与人工智能小组，计算机科学、电气与空间工程系）
Geometric Look-Angle Shaping Strategy for Enclosed Inspection
SYSTEC – Research Centre for Systems and Technologies（SYSTEC系统与技术研究中心）；ARISE – Advanced Production and Intelligent Systems（ARISE先进生产与智能系统）；Faculdade de Engenharia, Universidade do Porto（工程学院，葡萄牙波尔图大学）
