scholarly journals Development of Path Planning Algorithm of Centipede Inspired Wheeled Robot in Presence of Static and Moving Obstacles Using ModifiedCritical-SnakeBug Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 95
Author(s):  
Subir Kumar Das ◽  
Ajoy Kumar Dutta ◽  
Subir Kumar Debnath
Keyword(s):  
Path Planning ◽  
Real Life ◽  
Real Life Situation ◽  
Planning Algorithm ◽  
Dynamic Obstacle ◽  
Local Path ◽  
Stiff Body ◽  
Almost All ◽  
Path Planning Algorithm ◽  
Adaptation Ability

<p>Path planning for a movable robot in real life situation has been widely cultivated and become research interest for last few decades. Biomimetic robots have increased attraction for their capability to develop various kind of walking in order to navigate in different environment. To meet this requirement of natural insect locomotion has enabled the development of composite tiny robots. Almost all insect-scale legged robots take motivation from stiff-body hexapods; though, a different distinctive organism we find in nature is centipede, distinguished by its numerous legs and pliable body. This uniqueness is anticipated to present performance benefits to build robot of the said type in terms of swiftness, steadiness, toughness, and adaptation ability.</p>This paper proposes a local path planning algorithm of multiple rake centipede inspired robot namely ModifiedCritical-SnakeBug(MCSB) algorithm. Algorithm tries to avoid static and dynamic obstacle both. The results demonstrate the capability of the algorithm.

scholarly journals 2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuexi Zhang ◽  
Jiajun Lai ◽  
Dongliang Xu ◽  
Huaijun Li ◽  
Minyue Fu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Basic System ◽  
Rescue Robot ◽  
Planning Algorithm ◽  
Local Path ◽  
Slam Algorithm ◽  
Path Planning Algorithm

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

scholarly journals A Bi-Level Path Planning Algorithm for Multi-AGV Routing Problem

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1351
Author(s):  
Zhiheng Yuan ◽  
Zhengmao Yang ◽  
Lingling Lv ◽  
Yanjun Shi
Keyword(s):  
Path Planning ◽  
Random Trees ◽  
Dijkstra Algorithm ◽  
A Algorithm ◽  
Routing Problem ◽  
Agv Routing ◽  
Planning Algorithm ◽  
Local Grid ◽  
Local Path ◽  
Path Planning Algorithm

Avoiding the multi-automated guided vehicle (AGV) path conflicts is of importance for the efficiency of the AGV system, and we propose a bi-level path planning algorithm to optimize the routing of multi-AGVs. In the first level, we propose an improved A* algorithm to plan the AGV global path in the global topology map, which aims to make the path shortest and reduce the AGV path conflicts as much as possible. In the second level, we present the dynamic rapidly-exploring random trees (RRT) algorithm with kinematic constraints to obtain the passable local path with collisions in the local grid map. Compared to the Dijkstra algorithm and classic A* algorithm, the simulation results showed that the proposed bi-level path planning algorithm performed well in terms of the search efficiency, significantly reducing the incidence of multiple AGV path conflicts.

A smooth local path planning algorithm based on modified visibility graph

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740091 ◽  
Author(s):  
Taizhi Lv ◽  
Maoyan Feng
Keyword(s):  
Path Planning ◽  
Simulation Experiment ◽  
Visibility Graph ◽  
Local Path Planning ◽  
Spline Curves ◽  
Smooth Path ◽  
Planning Algorithm ◽  
Path Search ◽  
Local Path ◽  
Path Planning Algorithm

Path planning is an essential and inevitable problem in robotics. Trapping in local minima and discontinuities often exist in local path planning. To overcome these drawbacks, this paper presents a smooth path planning algorithm based on modified visibility graph. This algorithm consists of three steps: (1) polygons are generated from detected obstacles; (2) a collision-free path is found by simultaneous visibility graph construction and path search by A[Formula: see text] (SVGA); (3) the path is smoothed by B-spline curves and particle swarm optimization (PSO). Simulation experiment results show the effectiveness of this algorithm, and a smooth path can be found fleetly.

Dynamic Path Planning for Robot Navigation Using Sonor Mapping and Neural Networks

1997 ◽  
Vol 119 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Won Soo Yun ◽  
Dong Woo Cho ◽  
Yoon Su Baek
Keyword(s):  
Neural Networks ◽  
Path Planning ◽  
Mobile Robot ◽  
Local Planning ◽  
Sensor Model ◽  
Planning Algorithm ◽  
Local Path ◽  
Time Varying Environment ◽  
Path Planning Algorithm ◽  
Global And Local

This paper presents a new path planning algorithm for safe navigation of a mobile robot in dynamic as well as static environments. The certainty grid concept is adopted to represent the robot’s surroundings and a simple sensor model is developed for fast acquisition of environmental information. The proposed system integrates global and local path planning and has been implemented in a partially known structured environment without loss of generality for an indoor mobile robot. The global planner finds the initial path based on Dijkstra’s algorithm, while the local planning scheme uses three neural networks to follow the initial global path and avoid colliding with static and moving obstacles. Effectiveness of these algorithms is illustrated through simulation and experiment using a real robot. The results show that the proposed algorithm can be efficiently implemented in a time varying environment.

Research on local path planning based on improved RRT algorithm

2021 ◽  
pp. 095440702199362
Author(s):  
Changfu Zong ◽  
Xiaojian Han ◽  
Dong Zhang ◽  
Yang Liu ◽  
Weiqiang Zhao ◽  
...  
Keyword(s):  
Path Planning ◽  
Vehicle Dynamics ◽  
Simulation Software ◽  
Tracking Algorithm ◽  
Expansion Phase ◽  
Local Path Planning ◽  
Planning Algorithm ◽  
Local Path ◽  
Path Planning Algorithm ◽  
Actual Size

In order to solve the local path planning of self-driving car in the structured road environment, an improved path planning algorithm named Regional-Sampling RRT (RS-RRT) algorithm was proposed for obstacle avoidance conditions. Gaussian distribution sampling and local biasing sampling were integrated to improve the search efficiency in the sampling phase. In the expansion phase, considering the actual size of the vehicle and obstacles, combined with the goal of safety and comfort, the separating axis theorem (SAT) method and vehicle dynamics were used to detect the collision among vehicle and surrounding obstacles in real time. In the post-processing stage, the driver’s driving consensus and path smoothing algorithm were combined to correct the planning path. In order to track the generated path, the MPC tracking algorithm was designed based on the Four-Wheel-Independent Electric Vehicle (FWIEV) model. The co-simulation software platform of CarSim and MATLAB/Simulink was employed to verify the effectiveness and feasibility of the path planning and tracking algorithm. The results show that compared with basic RRT and Goal-biasing RRT, the proposed RS-RRT algorithm has advantages in terms of number of nodes, path length and running time. The generated path can meet the FWIEV dynamics and path tracking requirements.

Sign in / Sign up

Export Citation Format

Share Document