scholarly journals Hierarchical Weighting Vicsek Model for Flocking Navigation of Drones

Drones ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 74
Author(s):  
Xingyu Liu ◽  
Xiaojia Xiang ◽  
Yuan Chang ◽  
Chao Yan ◽  
Han Zhou ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Path Following ◽  
Convergence Speed ◽  
Regulation Mechanism ◽  
Simulation Experiments ◽  
Interaction Radius ◽  
Vicsek Model ◽  
Weighting Mechanism

Flocking navigation, involving alignment-guaranteed path following and collision avoidance against obstacles, remains to be a challenging task for drones. In this paper, we investigate how to implement flocking navigation when only one drone in the swarm masters the predetermined path, instead of all drones mastering their routes. Specifically, this paper proposes a hierarchical weighting Vicsek model (WVEM), which consists of a hierarchical weighting mechanism and a layer regulation mechanism. Based on the hierarchical mechanism, all drones are divided into three layers and the drones at different layers are assigned with different weights to guarantee the convergence speed of alignment. The layer regulation mechanism is developed to realize a more flexible obstacle avoidance. We analyze the influence of the WVEM parameters such as weighting value and interaction radius, and demonstrate the flocking navigation performance through a series of simulation experiments.

scholarly journals Towards Flocking Navigation and Obstacle Avoidance for Multi-UAV Systems through Hierarchical Weighting Vicsek Model

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 286
Author(s):  
Xingyu Liu ◽  
Chao Yan ◽  
Han Zhou ◽  
Yuan Chang ◽  
Xiaojia Xiang ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
High Performance ◽  
Local Information ◽  
Convergence Time ◽  
Complex Environments ◽  
System Safety ◽  
Vicsek Model ◽  
Aerial Vehicle ◽  
Weighting Mechanism ◽  
Multi Uav

Flocking navigation and obstacle avoidance in complex environments remain challenging for multiple unmanned aerial vehicle (multi-UAV) systems, especially when only one UAV (termed as information UAV) knows the predetermined path and the communication range is limited. To this end, we propose a hierarchical weighting Vicsek model (HWVEM). In this model, a hierarchical weighting mechanism and an obstacle avoidance mechanism are designed. Based on the hierarchical weighting mechanism, all the UAVs are divided into different layers, and assigned with different weights according to the layer to which they belong. The purpose is to align the rest of UAVs with the information UAV more efficiently. Subsequently, the obstacle avoidance mechanism that utilizes only the local information is developed to ensure the system safety in an environment filled with obstacles differing in size and shape. A series of simulations have been conducted to demonstrate the high performance of HWVEM in terms of convergence time, success rate, and safety.

scholarly journals NAVIGATION OF MOBILE ROBOT- ALGORITHM FOR PATH PLANNING & COLLISION AVOIDANCE- A REVIEW

2017 ◽  
Vol 5 (1) ◽  
pp. 198-205 ◽  
Author(s):  
V. Keerthana ◽  
C. Kiruthiga ◽  
P. Kiruthika ◽  
V. Sowmiya ◽  
R. Manikadan
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Back Propagation ◽  
Path Following ◽  
Robot System ◽  
Robot Systems ◽  
Line Following

The field of autonomous mobile robotics has recently gained many researchers’ interests. Due to the specific needs required by various applications of mobile robot systems, especially in navigation, designing a real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective of our project is applications based mobile robot systems, especially in navigation, designing real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective behind using the obstacle avoidance approach is to obtain a collision-free trajectory from the starting point to the target in monitoring environments. The ability of the robot to follow a path, detects obstacles, and navigates around them to avoid collision. It also shows that the robot has been successfully following very congested curves and has avoided any obstacle that emerged on its path. Motion planning that allows the robot to reach its target without colliding with any obstacles that may exist in its path. To avoid collision in the mobile robot environment, providing a path planning& line following approach. Line following, path planning, collision avoidance, back propagation, improved memory, detecting long distance obstacles. Cheap and economical than the former one. Also work with back propagation technique.

scholarly journals A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV’s Operation Scenario

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1069
Author(s):  
Shibbir Ahmed ◽  
Baijing Qiu ◽  
Fiaz Ahmad ◽  
Chun-Wei Kong ◽  
Huang Xin
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
State Of The Art ◽  
Obstacle Detection ◽  
Crop Monitoring ◽  
Data Intensive ◽  
Structural Details ◽  
Dynamic Operating ◽  
New Generation ◽  
The Internet Of Things

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

Robot obstacle avoidance system using deep reinforcement learning

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaojun Zhu ◽  
Yinghao Liang ◽  
Hanxu Sun ◽  
Xueqian Wang ◽  
Bin Ren
Keyword(s):  
Reinforcement Learning ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Learning Algorithm ◽  
Optimal Path ◽  
Environmental Parameters ◽  
Working Environment ◽  
Content Type ◽  
Practical Applications ◽  
Human Operators

Purpose Most manufacturing plants choose the easy way of completely separating human operators from robots to prevent accidents, but as a result, it dramatically affects the overall quality and speed that is expected from human–robot collaboration. It is not an easy task to ensure human safety when he/she has entered a robot’s workspace, and the unstructured nature of those working environments makes it even harder. The purpose of this paper is to propose a real-time robot collision avoidance method to alleviate this problem. Design/methodology/approach In this paper, a model is trained to learn the direct control commands from the raw depth images through self-supervised reinforcement learning algorithm. To reduce the effect of sample inefficiency and safety during initial training, a virtual reality platform is used to simulate a natural working environment and generate obstacle avoidance data for training. To ensure a smooth transfer to a real robot, the automatic domain randomization technique is used to generate randomly distributed environmental parameters through the obstacle avoidance simulation of virtual robots in the virtual environment, contributing to better performance in the natural environment. Findings The method has been tested in both simulations with a real UR3 robot for several practical applications. The results of this paper indicate that the proposed approach can effectively make the robot safety-aware and learn how to divert its trajectory to avoid accidents with humans within the workspace. Research limitations/implications The method has been tested in both simulations with a real UR3 robot in several practical applications. The results indicate that the proposed approach can effectively make the robot be aware of safety and learn how to change its trajectory to avoid accidents with persons within the workspace. Originality/value This paper provides a novel collision avoidance framework that allows robots to work alongside human operators in unstructured and complex environments. The method uses end-to-end policy training to directly extract the optimal path from the visual inputs for the scene.

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 Path planning of lunar robot based on dynamic adaptive ant colony algorithm and obstacle avoidance

2020 ◽  
Vol 17 (3) ◽  
pp. 172988141989897 ◽  
Author(s):  
Shinan Zhu ◽  
Weiyi Zhu ◽  
Xueqin Zhang ◽  
Tao Cao
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Ant Colony Algorithm ◽  
Global Search ◽  
Convergence Speed ◽  
Ant Colony ◽  
Local Optimum ◽  
Adaptive Potential ◽  
Avoidance Strategy

Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely and accurately. Aiming at the shortest path and the least energy consumption, an adaptive potential field ant colony algorithm suitable for path planning of lunar robot is proposed to solve the problems of slow convergence speed and easy to fall into local optimum of ant colony algorithm. This algorithm combines the artificial potential field method with ant colony algorithm, introduces the inducement heuristic factor, and adjusts the state transition rule of the ant colony algorithm dynamically, so that the algorithm has higher global search ability and faster convergence speed. After getting the planned path, a dynamic obstacle avoidance strategy is designed according to the predictable and unpredictable obstacles. Especially a geometric method based on moving route is used to detect the unpredictable obstacles and realize the avoidance of dynamic obstacles. The experimental results show that the improved adaptive potential field ant colony algorithm has higher global search ability and faster convergence speed. The designed obstacle avoidance strategy can effectively judge whether there will be collision and take obstacle avoidance measures.

scholarly journals Edge-weighted consensus-based formation control strategy with collision avoidance

Robotica ◽  
2014 ◽  
Vol 33 (2) ◽  
pp. 332-347 ◽  
Author(s):  
Riccardo Falconi ◽  
Lorenzo Sabattini ◽  
Cristian Secchi ◽  
Cesare Fantuzzi ◽  
Claudio Melchiorri
Keyword(s):  
Mobile Robots ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Formation Control ◽  
Weighted Graphs ◽  
Wheeled Robots ◽  
Unknown Environments ◽  
Multi Robot

SUMMARYIn this paper, a consensus-based control strategy is presented to gather formation for a group of differential-wheeled robots. The formation shape and the avoidance of collisions between robots are obtained by exploiting the properties of weighted graphs. Since mobile robots are supposed to move in unknown environments, the presented approach to multi-robot coordination has been extended in order to include obstacle avoidance. The effectiveness of the proposed control strategy has been demonstrated by means of analytical proofs. Moreover, results of simulations and experiments on real robots are provided for validation purposes.

On the Problem of Constrained Path Following For Manipulators

1988 ◽  
Vol 110 (4) ◽  
pp. 443-448
Author(s):  
A. Sankaranarayanan ◽  
M. Vidyasagar
Keyword(s):  
Collision Avoidance ◽  
Force Control ◽  
Robot Manipulator ◽  
Sufficient Conditions ◽  
Path Following ◽  
Necessary And Sufficient Conditions ◽  
End Effector ◽  
Circular Contour ◽  
Necessary And Sufficient

Force Control involves moving the end-effector of a robot manipulator on the surface of an object while ensuring that no other part of the manipulator collides with the object. Suppose C is a given contour to be followed. If the end-effector can move between two points a and b on C while meeting the collision avoidance requirement, we can say that a path exists between a and b. We begin by considering a planar manipulator and a circular contour and derive the necessary and sufficient conditions for a path to exist between a pair of points. By extending these ideas, sufficient conditions are derived for a noncircular contour. The advantages of a (kinematically redundant) 3-link planar manipulator over a 2-link manipulator are pointed out. Finally, we consider spatial manipulators and derive the necessary and sufficient conditions for the case where the contour lies on the surface of a sphere.

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