scholarly journals RL and ANN Based Modular Path Planning Controller for Resource-Constrained Robots in the Indoor Complex Dynamic Environment

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 74557-74568 ◽  
Author(s):  
Zakir Ullah ◽  
Zhiwei Xu ◽  
Lei Zhang ◽  
Libo Zhang ◽  
Waheed Ullah
Keyword(s):  
Path Planning ◽  
Dynamic Environment ◽  
Resource Constrained ◽  
Complex Dynamic ◽  
Constrained Robots

scholarly journals A Dynamic Path Planning Method for Social Robots in the Home Environment

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1173 ◽  
Author(s):  
Chen Zhang ◽  
Lelai Zhou ◽  
Yibin Li ◽  
Yong Fan
Keyword(s):  
Path Planning ◽  
Home Environment ◽  
Dynamic Environment ◽  
Social Robots ◽  
Planning Problem ◽  
Complex Dynamic ◽  
3D Space ◽  
Dynamic Path Planning ◽  
The Social ◽  
Feasible Path

The home environment is a typical dynamic environment with moveable obstacles. The social robots working in home need to search for feasible paths in this complex dynamic environment. In this work, we propose an improved RRT algorithm to plan feasible path in home environment. The algorithm pre-builds a tree that covers the whole map and maintains the effectiveness of all nodes with branch pruning, reconnection, and regrowth process. The method forms a path by searching the nearest node in the tree and then quickly accessing the nodes near the destination. Due to the effectiveness-maintaining process, the proposed method can effectively deal with the complex dynamic environment where the destination and multiple moving obstacles change simultaneously. In addition, our method can be extended to the path-planning problem in 3D space. The simulation experiments verify the effectiveness of the algorithm.

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.

Backtracking Hybrid Α* for Resource Constrained Path Planning

2022 ◽  
Author(s):  
Bryce T. Ford ◽  
Rachit Aggarwal ◽  
Mrinal Kumar ◽  
Satyanarayana G. Manyam ◽  
David Casbeer ◽  
...  
Keyword(s):  
Path Planning ◽  
Resource Constrained

A method for avoiding obstacles of a self-driving carin the dynamic environment based on model predictive control

2021 ◽  
Author(s):  
N.P. Demenkov ◽  
Kai Zou
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Urban Environment ◽  
Predictive Control ◽  
Potential Field ◽  
Dynamic Environment ◽  
Field Method ◽  
Artificial Potential Field ◽  
Physical Constraints ◽  
Local Path

The paper discusses the problem of obstacle avoidance of a self-driving car in urban road conditions. The artificial potential field method is used to simulate traffic lanes and cars in a road environment. The characteristics of the urban environment, as well as the features and disadvantages of existing methods based on the structure of planning-tracking, are analyzed. A method of local path planning is developed, based on the idea of an artificial potential field and model predictive control in order to unify the process of path planning and tracking to effectively cope with the dynamic urban environment. The potential field functions are introduced into the path planning task as constraints. Based on model predictive control, a path planning controller is developed, combined with the physical constraints of the vehicle, to avoid obstacles and execute the expected commands from the top level as the target for the task. A joint simulation was performed using MATLAB and CarSim programs to test the feasibility of the proposed path planning method. The results show the effectiveness of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document