scholarly journals Autonomous Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on an Improved Velocity Obstacle Method

2021 ◽  
Vol 10 (9) ◽  
pp. 618
Author(s):  
Jia Ren ◽  
Jing Zhang ◽  
Yani Cui
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Collision Detection ◽  
Particle Swarm Algorithm ◽  
Unmanned Surface Vehicles ◽  
Detection Model ◽  
Planning Algorithm ◽  
Avoidance Strategy ◽  
Vessel Motion ◽  
Velocity Obstacle

Focusing on the collision avoidance problem for Unmanned Surface Vehicles (USVs) in the scenario of multi-vessel encounters, a USV autonomous obstacle avoidance algorithm based on the improved velocity obstacle method is proposed. The algorithm is composed of two parts: a multi-vessel encounter collision detection model and a path re-planning algorithm. The multi-vessel encounter collision detection model draws on the idea of the velocity obstacle method through the integration of characteristics such as the USV dynamic model in the marine environment, the encountering vessel motion model, and the International Regulations for Preventing Collisions at Sea (COLREGS) to obtain the velocity obstacle region in the scenario of USV and multi-vessel encounters. On this basis, two constraint conditions for the motion state space of USV obstacle avoidance behavior and the velocity obstacle region are added to the dynamic window algorithm to complete a USV collision risk assessment and generate a collision avoidance strategy set. The path re-planning algorithm is based on the premise of the minimum resource cost and uses an improved particle swarm algorithm to obtain the optimal USV control strategy in the collision avoidance strategy set and complete USV path re-planning. Simulation results show that the algorithm can enable USVs to safely evade multiple short-range dynamic targets under COLREGS.

scholarly journals Obstacle Avoidace Robot Using LabView

2015 ◽  
Vol 4 (3) ◽  
pp. 164
Author(s):  
Tasher Ali Sheikh ◽  
Swacheta Dutta ◽  
Smriti Baruah ◽  
Pooja Sharma ◽  
Sahadev Roy
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Autonomous Robotics ◽  
Continuous Transition ◽  
Heavy Burden ◽  
Avoidance Strategy ◽  
Small Period ◽  
Specific Amount

The concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system.

scholarly journals The Obstacle-Avoidance Path Planning for UAV Based on IOCAD

2020 ◽  
Vol 38 (2) ◽  
pp. 238-245
Author(s):  
Qiqian Zhang ◽  
Weiwei Xu ◽  
Honghai Zhang ◽  
Han Li
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Rough Set Theory ◽  
Grid Method ◽  
Flight Path ◽  
Ray Method ◽  
Detection Model ◽  
Safety Distance ◽  
Planning Algorithm ◽  
Grid Length

To plan the path for UAV flying in the complex, dense and irregular obstacles environment, this paper proposed an obstacle collision-avoidance detection model and designed an UAV path planning algorithm based on irregular obstacles collision-avoidance detection (IOCAD), which includes irregular obstacles pretreatment method. The proposed method uses the grid method to model the environment. Rough set theory and convexity filling are used to pretreat the obstacles, and the ray method is used to select the available points. The intersection detection and the distance detection are held for the obstacle to the flight path. The objective function minimizes the distance from the obstacle to the flight path to get planned paths. The simulation results show that the proposed method can effectively plan the paths with the constraints of the assumed environment and UAV performances. It is shown that the performance of the proposed method is sensitive to the grid length and safety distance. The optimized values for the grid length and safety distance are 0.5 km and 0.4 km respectively.

Velocity Obstacle-Based Collision Avoidance and Motion Planning Framework for Connected and Automated Vehicles

2022 ◽  
pp. 036119812110702
Author(s):  
Shunchao Wang ◽  
Zhibin Li ◽  
Bingtong Wang ◽  
Jingfeng Ma ◽  
Jingcai Yu
Keyword(s):  
Motion Planning ◽  
Collision Avoidance ◽  
Motion Tracking ◽  
Collision Risk ◽  
Automated Vehicles ◽  
Vehicle Collision ◽  
Planning Framework ◽  
Planning Algorithm ◽  
Velocity Obstacle ◽  
Vehicle Dynamic Model

This study proposes a novel collision avoidance and motion planning framework for connected and automated vehicles based on an improved velocity obstacle (VO) method. The controller framework consists of two parts, that is, collision avoidance method and motion planning algorithm. The VO algorithm is introduced to deduce the velocity conditions of a vehicle collision. A collision risk potential field (CRPF) is constructed to modify the collision area calculated by the VO algorithm. A vehicle dynamic model is presented to predict vehicle moving states and trajectories. A model predictive control (MPC)-based motion tracking controller is employed to plan collision-avoidance path according to the collision-free principles deduced by the modified VO method. Five simulation scenarios are designed and conducted to demonstrate the control maneuver of the proposed controller framework. The results show that the constructed CRPF can accurately represent the collision risk distribution of the vehicles with different attributes and motion states. The proposed framework can effectively handle the maneuver of obstacle avoidance, lane change, and emergency response. The controller framework also presents good performance to avoid crashes under different levels of collision risk strength.

scholarly journals Collision avoidance planning for unmanned surface vehicle based on eccentric expansion

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985194 ◽  
Author(s):  
Lifei Song ◽  
Zhuo Chen ◽  
Zaopeng Dong ◽  
Zuquan Xiang ◽  
Yunsheng Mao ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Physical Simulation ◽  
Risk Level ◽  
Unmanned Surface Vehicle ◽  
Unmanned Surface Vehicles ◽  
Automatic Driving ◽  
International Regulations ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

The International Regulations for Preventing Collisions at Sea (COLREGS) specify certain navigation rules for ships at risk for collision. Theoretically, the safety of unmanned surface vehicles and traffic boats would be guaranteed when they comply with the COLREGS. However, if traffic boats do not comply with the demands of the convention, thereby increasing the danger level, then adhering to the COLREGS may be dangerous for the unmanned surface vehicle. In this article, a dynamic obstacle avoidance algorithm for unmanned surface vehicles based on eccentric expansion was developed. This algorithm is used to solve the possible failure of collision avoidance when the unmanned surface vehicle invariably obeys the COLREGS during the avoidance process. An obstacle avoidance model based on the velocity obstacle method was established. Thereafter, an eccentric expansion operation on traffic boats was proposed to ensure a reasonable balance between safety and the rules of COLREGS. The expansion parameters were set according to the rules of COLREGS and the risk level of collision. Then, the collision avoidance parameters were calculated based on the aforementioned motion model. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under different situations. Results show the validity, reliability and intellectuality of the algorithm. This research can be used for intelligent collision avoidance of unmanned surface vehicle and other automatic driving ships.

scholarly journals Local Route Planning for Collision Avoidance of Maritime Autonomous Surface Ships in Compliance with COLREGs Rules

2021 ◽  
Vol 14 (1) ◽  
pp. 198
Author(s):  
Ho Namgung
Keyword(s):  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Human Life ◽  
Risk Index ◽  
Route Planning ◽  
Inference System ◽  
Surface Ship ◽  
International Regulations ◽  
Planning Algorithm ◽  
Velocity Obstacle

A maritime autonomous surface ship (MASS) ensures safety and effectiveness during navigation using its ability to prevent collisions with a nearby target ship (TS). This avoids the loss of human life and property. Therefore, collision avoidance of MASSs has been actively researched recently. However, previous studies did not consider all factors crucial to collision avoidance in compliance with the International Regulations for Preventing Collisions at Sea (COLREGs) Rules 5, 7, 8, and 13–17. In this study, a local route-planning algorithm that takes collision-avoidance actions in compliance with COLREGs Rules using a fuzzy inference system based on near-collision (FIS-NC), ship domain (SD), and velocity obstacle (VO) is proposed. FIS-NC is used to infer the collision risk index (CRI) and determine the time point for collision avoidance. Following this, I extended the VO using the SD to secure the minimum safe distance between the MASS and the TS when they pass each other. Unlike previous methods, the proposed algorithm can be used to perform safe and efficient navigation in terms of near-collision accidents, inferred CRI, and deviation from the course angle route by taking collision-avoidance actions in compliance with COLREGs Rules 5, 7, 8, and 13–17.

scholarly journals Analysis of Obstacle Avoidance Strategy for Dual-Arm Robot Based on Speed Field with Improved Artificial Potential Field Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1850
Author(s):  
Hui Zhang ◽  
Yongfei Zhu ◽  
Xuefei Liu ◽  
Xiangrong Xu
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Planning Methods ◽  
Avoidance Strategy ◽  
Dual Arm Robot ◽  
Dual Arm ◽  
Avoidance Problem

In recent years, dual-arm robots have been favored in various industries due to their excellent coordinated operability. One of the focused areas of study on dual-arm robots is obstacle avoidance, namely path planning. Among the existing path planning methods, the artificial potential field (APF) algorithm is widely applied in obstacle avoidance for its simplicity, practicability, and good real-time performance over other planning methods. However, APF is firstly proposed to solve the obstacle avoidance problem of mobile robot in plane, and thus has some limitations such as being prone to fall into local minimum, not being applicable when dynamic obstacles are encountered. Therefore, an obstacle avoidance strategy for a dual-arm robot based on speed field with improved artificial potential field algorithm is proposed. In our method, the APF algorithm is used to establish the attraction and repulsion functions of the robotic manipulator, and then the concepts of attraction and repulsion speed are introduced. The attraction and repulsion functions are converted into the attraction and repulsion speed functions, which mapped to the joint space. By using the Jacobian matrix and its inverse to establish the differential velocity function of joint motion, as well as comparing it with the set collision distance threshold between two robotic manipulators of robot, the collision avoidance can be solved. Meanwhile, after introducing a new repulsion function and adding virtual constraint points to eliminate existing limitations, APF is also improved. The correctness and effectiveness of the proposed method in the self-collision avoidance problem of a dual-arm robot are validated in MATLAB and Adams simulation environment.

scholarly journals Experimental validation of a velocity obstacle based collision avoidance algorithm for unmanned surface vehicles

2019 ◽  
Vol 52 (21) ◽  
pp. 329-334
Author(s):  
Yonghoon Cho ◽  
Jungwook Han ◽  
Jinwhan Kim ◽  
Philyeob Lee ◽  
Shin-Bae Park
Keyword(s):  
Collision Avoidance ◽  
Experimental Validation ◽  
Unmanned Surface Vehicles ◽  
Velocity Obstacle

scholarly journals Research on Path Planning Algorithm for Crowd Evacuation

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1339
Author(s):  
Zhenfei Wang ◽  
Chuchu Zhang ◽  
Junfeng Wang ◽  
Zhiyun Zheng ◽  
Lun Li
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Large Scale ◽  
Path Selection ◽  
Limited Area ◽  
Evacuation Time ◽  
Planning Algorithm ◽  
Crowd Evacuation ◽  
Avoidance Strategy ◽  
Path Planning Algorithm

In recent years, crowded stampede incidents have occurred frequently, resulting in more and more serious losses. The common cause of such incidents is that when large-scale populations gather in a limited area, the population is highly unstable. In emergency situations, only when the crowd reaches the safe exit as soon as possible within a limited evacuation time to complete evacuation can the loss and casualties be effectively reduced. Therefore, the safety evacuation management of people in public places in emergencies has become a hot topic in the field of public security. Based on the analysis of the factors affecting the crowd path selection, this paper proposes an improved path-planning algorithm based on BEME (Balanced Evacuation for Multiple Exits). And pedestrian evacuation simulation is carried out in multi-exit symmetrical facilities. First, this paper optimizes the update method of the GSDL list in the BEME algorithm as the basis for evacuating pedestrians to choose an exit. Second, the collision between pedestrians is solved by defining the movement rule and collision avoidance strategy. Finally, the algorithm is compared with BEME and traditional path-planning algorithms. The results show that the algorithm can further shorten the global evacuation distance of the symmetrical evacuation scene, effectively balance the number of pedestrians at each exit and reduce the evacuation time. In addition, this improved algorithm uses a collision avoidance strategy to solve the collision and congestion problems in path planning, which helps to maximize evacuation efficiency. Whether the setting of the scene or the setting of the exit, all studies are based on symmetric implementation. This is more in line with the crowd evacuation in the real scene, making the experimental results more meaningful.

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