Deep-Sarsa Based Multi-UAV Path Planning and Obstacle Avoidance in a Dynamic Environment

2018 ◽  
pp. 102-111 ◽  
Author(s):  
Wei Luo ◽  
Qirong Tang ◽  
Changhong Fu ◽  
Peter Eberhard
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Multi Uav

scholarly journals Path planning method with obstacle avoidance for manipulators in dynamic environment

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141882022 ◽  
Author(s):  
Gang Chen ◽  
Dan Liu ◽  
Yifan Wang ◽  
Qingxuan Jia ◽  
Xiaodong Zhang
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Collision Detection ◽  
Point Cloud ◽  
Cloud Model ◽  
Dynamic Environment ◽  
Collision Probability ◽  
Point Cloud Model ◽  
Bounding Boxes

Obstacle avoidance is of great importance for path planning of manipulators in dynamic environment. To help manipulators successfully perform tasks, a method of path planning with obstacle avoidance is proposed in this article. It consists of two consecutive phases, namely, collision detection and obstacle-avoidance path planning. The collision detection is realized by establishing point-cloud model and testing intersection of axis-aligned bounding boxes trees, while obstacle-avoidance path planning is achieved through preplanning a global path and adjusting it in real time. This article has the following contributions. The point-cloud model is of high resolution while the speed of collision detection is improved, and collision points can be found exactly. The preplanned global path is optimized based on the improved D-star algorithm, which reduces inflection points and decreases collision probability. The real-time path adjusting strategy satisfies the requirement of reachability and obstacle avoidance for manipulators in dynamic environment. Simulations and experiments are carried out to evaluate the validity of the proposed method, and the method is available to manipulators of any degree of freedom in dynamic environment.

scholarly journals Path Planning and Obstacle Avoidance for Mobile Robots in a Dynamic Environment

2014 ◽  
Vol 6 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Liping Sun ◽  
Yonglong Luo ◽  
Xintao Ding ◽  
Longlong Wu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Dynamic Environment

scholarly journals Real-Time Hybrid Navigation System-Based Path Planning and Obstacle Avoidance for Mobile Robots

2020 ◽  
Vol 10 (10) ◽  
pp. 3355 ◽  
Author(s):  
Phan Gia Luan ◽  
Nguyen Truong Thinh
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Heuristic Algorithm ◽  
Navigation System ◽  
Dynamic Environment ◽  
Model Parameters ◽  
Moving Frames ◽  
Proposed Model ◽  
Multi Agent

In this work, we present a complete hybrid navigation system for a two-wheel differential drive mobile robot that includes static-environment- global-path planning and dynamic environment obstacle-avoidance tasks. By the given map, we propose a multi-agent A-heuristic algorithm for finding the optimal obstacle-free path. The result is less time-consuming and involves fewer changes in path length when dealing with multiple agents than the ordinary A-heuristic algorithm. The obtained path was smoothed based on curvature-continuous piecewise cubic Bézier curve (C2 PCBC) before being used as a trajectory by the robot. In the second task of the robot, we supposed any unforeseen obstacles were recognized and their moving frames were estimated by the sensors when the robot tracked on the trajectory. In order to adapt to the dynamic environment with the presence of constant velocity obstacles, a weighted-sum model (WSM) was employed. The 2D LiDAR data, the robot’s frame and the detected moving obstacle’s frame were collected and fed to the WSM during the movement of the robot. Through this information, the WSM chose a temporary target and a C2 PCBC-based subtrajectory was generated that led the robot to avoid the presented obstacle. Experimentally, the proposed model responded well in existing feasible solution cases with fine-tuned model parameters. We further provide the re-path algorithm that helped the robot track on the initial trajectory. The experimental results show the real-time performance of the system applied in our robot.

scholarly journals An Effective Dynamic Path Planning Approach for Mobile Robots Based on Ant Colony Fusion Dynamic Windows

Machines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 50
Author(s):  
Liwei Yang ◽  
Lixia Fu ◽  
Ping Li ◽  
Jianlin Mao ◽  
Ning Guo
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Ant Colony ◽  
Complex Dynamic ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Window Approach ◽  
Search Capability

To further improve the path planning of the mobile robot in complex dynamic environments, this paper proposes an enhanced hybrid algorithm by considering the excellent search capability of the ant colony optimization (ACO) for global paths and the advantages of the dynamic window approach (DWA) for local obstacle avoidance. Firstly, we establish a new dynamic environment model based on the motion characteristics of the obstacles. Secondly, we improve the traditional ACO from the pheromone update and heuristic function and then design a strategy to solve the deadlock problem. Considering the actual path requirements of the robot, a new path smoothing method is present. Finally, the robot modeled by DWA obtains navigation information from the global path, and we enhance its trajectory tracking capability and dynamic obstacle avoidance capability by improving the evaluation function. The simulation and experimental results show that our algorithm improves the robot's navigation capability, search capability, and dynamic obstacle avoidance capability in unknown and complex dynamic environments.

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