Article
Environmental Sciences
Chongyang Han, Weibin Wu, Xiwen Luo, Jiehao Li, Geert Verhoeven
Summary: This paper presents a navigation and obstacle avoidance system for agricultural robots based on LiDAR and a vision camera. The improved clustering algorithm and convex hull algorithm are used to analyze obstacle information in real time. Obstacle avoidance paths and course control methods are developed based on the dangerous zones of obstacles. Through color space analysis and feature analysis, the optimal HSV color component is selected to obtain the ideal vision-guided trajectory images. The proposed algorithm is proven to be effective and robust through obstacle avoidance experiments.
Article
Computer Science, Information Systems
Jingtao Qi, Liang Bai, Yandong Xiao, Yingmei Wei, Wansen Wu
Summary: The paper introduces a collective obstacle avoidance model VPDP based on visual perception, which achieves collective obstacle avoidance behavior through visual information between individuals. The model effectively maintains a safe distance and good coherence, showing robustness in parameter sensitivity analysis.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Wenxue Zhang, Dusan M. Stipanovic, Di Zhou
Summary: This paper presents a closed-form cooperative avoidance control design for 3-dimensional rigid-body agents, integrating collision risk with motion and posture information to improve efficiency and reliability of avoidance.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Nanoscience & Nanotechnology
Qiangwei Pang, Yongyong Zhu, Ye Chen, Deshi Wang, Wenkai Suo
Summary: This paper proposes a distributed Kalman model predictive control algorithm to address the perturbation of formation of multiple unmanned aerial vehicles (UAVs) subject to external disturbances and improve the accuracy of maintaining a formation in flight. The algorithm builds a UAV two-order discrete-time system model and devises a Kalman prediction model based on the standard prediction model. It determines the reference state of UAVs through desired formation configuration and neighbor Kalman optimal state estimation. A logarithmic barrier function is introduced to ensure flight safety considering the formation tracking error and input stability. Information is exchanged with neighbors using a directed and time-invariant communication topological structure. Sufficient conditions for the asymptotic stability of the formation system are defined using the Lyapunov stability theorem. Simulation results show that the algorithm effectively suppresses perturbations in the formation of UAVs caused by external disturbances, enabling the formation to handle conflicts between individual UAVs.
Article
Engineering, Marine
Zhilin Liu, Simeng Song, Shouzheng Yuan, Yingkai Ma, Zongxun Yao
Summary: This paper investigates the problems of path following and obstacle avoidance for unmanned surface vessels (USVs). An adaptive line-of-sight algorithm is used to determine the desired heading angle, and a Model Predictive Control method is employed to reduce lateral error. The event-triggered mechanism strategy is utilized to minimize the computational cost, and a linear extended state observer is used to compensate for external disturbances. An improved obstacle avoidance algorithm based on the geometric relationship is proposed. The results of simulation experiments demonstrate the effectiveness of the proposed approach in improving path following capability and security.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Marine
Haitong Xu, Miguel A. Hinostroza, C. Guedes Soares
Summary: This research presents a modified path-following control system for autonomous surface ships in the presence of static obstacles, which integrates path following and obstacle avoidance tasks as a whole. By utilizing a vector field method and the velocity obstacle algorithm, the system enables ships to safely navigate through obstacles and follow predefined paths simultaneously.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Diana D. Chin, David Lentink
Summary: This study reveals that Pacific parrotlets utilize drag to maneuver around obstacles while flying. They adjust their body angle and wing movement to redirect forces, relying on visual cues. This provides new insight into avian maneuvering and the role of drag in flight evolution.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Robotics
Amir Salimi Lafmejani, Hamed Farivarnejad, Spring Berman
Summary: The study proposes a gradient-based nonlinear control approach to stabilize nonholonomic robots to a target position in environments with and without obstacles, which can be adjusted by the desired convergence rate of the target position in both obstacle-free and obstacle environments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Engineering, Marine
Linling Wang, Xiaoyan Xu, Bing Han, Huapeng Zhang
Summary: In this paper, a multi-autonomous underwater vehicle (multi-AUV) formation control method with obstacle avoidance ability in 3D complex underwater environments based on an event-triggered model predictive control (EMPC) is proposed. The effectiveness and superiority of the proposed algorithm are confirmed via simulation and compared with those of other algorithms.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
A. Durand-Petiteville, V. Cadenat
Summary: This work proposes a Visual Predictive Control (VPC) scheme adapted to the navigation problem among static obstacles, addressing challenges such as accurate prediction models, long prediction horizon, and optimization problem evolution. The proposed approach improves prediction accuracy, integrates constraints, refines optimized trajectory, and achieves significantly faster performance compared to classical configurations.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Robotics
Naiyao Wang, Bo Zhang, Haixu Chi, Hua Wang, Sean Mcloone, Hongbo Liu
Summary: In this paper, the DUEL model is proposed to learn autonomous obstacle avoidance using binocular vision to perceive scene depth. The cognitive generation network generates obstacle avoidance policies, which are then optimized by the policy decision network referring to expert policies. The generated policies are transferred to the potential partition network for multi-modal obstacle avoidance. Experimental results demonstrate the effectiveness of the DUEL model.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
Article
Ergonomics
Ming Yue, Chao Fang, Hongzhi Zhang, Jinyong Shangguan
Summary: A driver-centered steering assist controller is proposed to reduce accidents caused by obstacles avoidance, with an adaptive authority allocation system and a concept of space collision risk introduced. The allocation of steering authorities is done adaptively based on SCR, and an autonomous steering controller using MPC and APF techniques is developed to aid the driver when necessary, showing feasibility and effectiveness in simulations.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Article
Computer Science, Artificial Intelligence
Lan Anh Trinh, Mikael Ekstrom, Baran Curuklu
Summary: This paper presents a novel path planning algorithm for multiple robots that ensures safe path planning by avoiding collisions among robots and between robots and humans. The algorithm selects the optimal configuration of paths by analyzing the traveling time of robots on different paths using Petri Nets.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Computer Science, Information Systems
Jia Wang, Rongtao Wang, Daohua Lu, Hao Zhou, Tianyi Tao
Summary: This study proposes an autonomous dynamic obstacle avoidance method for unmanned surface vehicles (USVs) based on the enhanced velocity obstacle method, and numerically demonstrates that it optimizes the heading angle, thereby avoiding the risk of ship rollover and achieving more accurate obstacle avoidance actions.
Article
Chemistry, Multidisciplinary
Gang Shao, Lei Wan, Huixi Xu
Summary: In this study, a design method is proposed for multiple AUVs that are distributed in an underwater area to work according to their own state and automatically avoid obstacles in order to reach the target. An optimal control method is introduced to achieve consensus among the AUVs and provide obstacle avoidance capability with minimal control effort. The distributed analytic optimal control law relies on local information generated by communication topology, ensuring the proposed behavior without requiring information from all AUVs. Simulation and experimentation were conducted to verify the consensus and obstacle avoidance effect.
APPLIED SCIENCES-BASEL
(2023)
