A Study on Global Path Planners Algorithms for the Simulated TurtleBot 3 Robot in ROS

Brasil, Pedro Medeiros de Assis; Pereira, F.; Cuadros, Marco Antônio de Souza Leite; Cukla, Anselmo Rafael; Gamarra, Daniel Fernando Tello

doi:10.1109/lars/sbr/wre51543.2020.9307003

Cited by 14 publications

(7 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Simulation results demonstrated the algorithm’s efficiency and smoothness compared to other algorithms. Practical validation was also attempted on the TurtleBot3 Waffle Pi mobile robot [ 15 ].…”

Section: Related Workmentioning

confidence: 99%

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning

Kabir,

Watanobe,

Islam

et al. 2024

Sensors

View full text Add to dashboard Cite

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance. The proposed adaptive cost function keeps track of the goal node and adaptively calculates the movement costs for quickly arriving at the goal node. Incorporating the adaptive cost function with a selected optimal RMB significantly reduces the searches of less impactful and redundant nodes, which improves the performance of the A* algorithm in terms of the number of search nodes and time complexity. To validate the performance and robustness of the proposed model, an extensive experiment was conducted. In the experiment, an open-source dataset featuring various types of grid maps was customized to incorporate the multiple map sizes and sets of source-to-destination nodes. According to the experiments, the proposed method demonstrated a remarkable improvement of 93.98% in the number of search nodes and 98.94% in time complexity compared to the conventional A* algorithm. The proposed model outperforms other state-of-the-art algorithms by keeping the path cost largely comparable. Additionally, an ROS experiment using a robot and lidar sensor data shows the improvement of the proposed method in a simulated laboratory environment.

show abstract

Section: Related Workmentioning

confidence: 99%

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning

Kabir,

Watanobe,

Islam

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Turning to more details, particularly in TurtleBot3, de Assis Brasil et al [10] evaluate global path planning between Dijkstra and A* with the same local path planner, DWA, for TurtleBot3 in the simulation that Dijkstra is slightly superior in the environment with the obstacle. Meanwhile, Cybulski et al [11] assess three local plans: (1) DWA, (2) EBand, (3) TEB as the extension of EBand, by accuracy and repeatability in the simulation and real research platform.…”

Section: A Navigation and Obstacle Avoidancementioning

confidence: 99%

“…Therefore, A* could be suitable for the hangar because it can reduce computation and time spent and still offer an optimal path. In addition, A* can ensure receiving the ideal path with one processing [10]. That could influence task achievement and repeatability.…”

Section: A Navigation and Obstacle Avoidancementioning

confidence: 99%

Navigation for a mobile robot to inspect aircraft

Mansakul

Fan

Tang

2023

2023 7th International Young Engineers Forum (YEF-ECE)

View full text Add to dashboard Cite

Preflight inspection is an important part of aircraft maintenance, as it does not affect only safety but also expenditure. In order to reduce the risks from human errors and the cost of operation, a mobile robot is introduced as an effective solution. This research examines navigation for aircraft inspection using a mobile robot. The two path planning methods, Dijkstra with DWA and A* with TEB, are compared by navigation performance in the simulation and three environments which are office, atrium, and hangar, to ensure that the robot is able to handle a variety of situations. In addition, an ultrasonic sensor was installed to perform obstacle avoidance and support LIDAR when it failed. The result is that both algorithms have their advantages depending on the purpose; if an accurate position is required, A* with TEB should be selected, while Dijkstra with DWA offers a smooth path and less time spent in small and complex environments. The notable parameters in navigation for the mobile robot, TurtleBot3, are presented, and limitations are detailed. The use of the autonomous mobile robot could support the operation with high precision and repeatability.

show abstract

“…Therefore, by employing the A* algorithm with its heuristic search strategy, this section achieves efficient and effective trajectory generating, ensuring safe and obstacle-free navigation for the robotic wheelchair in unknown environments. The details for the use of the A* algorithm in the ROS platform can be found in [29].…”

Section: The Global Path Planner Using A* Algorithmmentioning

confidence: 99%

Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs

Wang,

Cao,

Takanishi

2023

Robotics

View full text Add to dashboard Cite

In this work, the motion control of a robotic wheelchair to achieve safe and intelligent movement in an unknown scenario is proposed. The primary objective is to develop a comprehensive framework for a robotic wheelchair that combines a global path planner and a model predictive control (MPC) local controller. The A* algorithm is employed to generate a global path. To ensure safe and directional motion for the wheelchair user, an MPC local controller is implemented taking into account the via points generated by an approach combined with dual quaternions and spherical linear interpolation (SLERP). Dual quaternions are utilized for their simultaneous handling of rotation and translation, while SLERP enables smooth and continuous rotation interpolation by generating intermediate orientations between two specified orientations. The integration of these two methods optimizes navigation performance. The system is built on the Robot Operating System (ROS), with an electric wheelchair equipped with 3D-LiDAR serving as the hardware foundation. The experimental results reveal the effectiveness of the proposed method and demonstrate the ability of the robotic wheelchair to move safely from the initial position to the destination. This work contributes to the development of effective motion control for robotic wheelchairs, focusing on safety and improving the user experience when navigating in unknown environments.

show abstract

A Study on Global Path Planners Algorithms for the Simulated TurtleBot 3 Robot in ROS

Cited by 14 publications

References 6 publications

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning

Navigation for a mobile robot to inspect aircraft

Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs

Contact Info

Product

Resources

About