scholarly journals Foraging Task of Multiple Mobile Robots in a Dynamic Environment Using Adaptive Behavior in Crickets

2007 ◽  
Vol 19 (4) ◽  
pp. 466-473 ◽  
Author(s):  
Masatoshi Ashikaga ◽  
◽  
Mika Kikuchi ◽  
Tetsutaro Hiraguchi ◽  
Midori Sakura ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Adaptive Behavior ◽  
Dynamic Environment ◽  
Multiple Mobile Robots ◽  
Fighting Behavior ◽  
Simulation Results ◽  
Foraging Task

In this paper, we propose an algorithm for multiple mobile robots performing a foraging task. In the proposed algorithm, robots select behaviors based on their activities, which were adjusted by interaction with other robots and foods. The proposed algorithm was inspired by the mechanism governing the fighting behavior in male crickets. Simulation results showed that the algorithm is efficient in a dynamic environment.

Cooperative Towing With Multiple Robots

2008 ◽  
Author(s):  
Jonathan Fink ◽  
Peng Cheng ◽  
Vijay Kumar
Keyword(s):  
Mobile Robots ◽  
Dry Friction ◽  
Equations Of Motion ◽  
Static Model ◽  
Multiple Robots ◽  
Coordinated Motion ◽  
Multiple Mobile Robots ◽  
Basic Concepts ◽  
Simulation Results

In this paper, we address the cooperative towing of payloads by multiple mobile robots in the plane. Robots are attached via cables to a planar object or a pallet carrying a payload. Coordinated motion by the robots allow the payload to be manipulated through a planar, warehouse-like environment. We formulate a quasi-static model for manipulation and derive equations of motion that yield the motion of the payload for a prescribed motion of the robots in the presence of dry friction and tension constraints. We present experimental and simulation results that demonstrate the basic concepts.

scholarly journals A PSO-Optimized Reciprocal Velocity Obstacles Algorithm for Navigation of Multiple Mobile Robots

2015 ◽  
Vol 4 (1) ◽  
pp. 31
Author(s):  
Ziyad Allawi ◽  
Turki Abdalla
Keyword(s):  
Particle Swarm Optimization ◽  
Mobile Robots ◽  
Collision Avoidance ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Multiple Mobile Robots ◽  
Kinematic Constraints ◽  
Navigation Control ◽  
Simulation Results

In this paper, a new optimization method for the Reciprocal Velocity Obstacles (RVO) is proposed. It uses the well-known Particle Swarm Optimization (PSO) for navigation control of multiple mobile robots with kinematic constraints. The RVO is used for collision avoidance between the robots, while PSO is used to choose the best path for the robot maneuver to avoid colliding with other robots and to get to its goal faster. This method was applied on 24 mobile robots facing each other. Simulation results have shown that this method outperforms the ordinary RVO when the path is heuristically chosen.

A Novel Algorithm for Path Planning of Mobile Robots in Dynamic Environment

2011 ◽  
Vol 345 ◽  
pp. 370-374
Author(s):  
Xiao Mei Ning ◽  
Zhan Chun Ma ◽  
Li Guo
Keyword(s):  
Evolutionary Algorithms ◽  
Path Planning ◽  
Mobile Robots ◽  
Cloud Model ◽  
Dynamic Environment ◽  
One Dimensional ◽  
Search Results ◽  
Simulation Results ◽  
Evolutionary Operators ◽  
Novel Algorithm

Aimed to accuracy and convergence of Evolutionary Algorithms for path planning of robots in dynamic environment, this paper integrated cloud model into evolutionary algorithm to improved evolutionary operators. One-dimensional cloud operator was used evolution and mutation, at the same time the previous search results were used. Simulation results show that the method is effective in performance.

scholarly journals Neural dynamics based complete grid coverage by single and multiple mobile robots

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Arindam Singha ◽  
Anjan Kumar Ray ◽  
Arun Baran Samaddar
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Neural Dynamics ◽  
Grid Cells ◽  
Complete Coverage ◽  
Multiple Mobile Robots ◽  
Dead End ◽  
Simulation Results ◽  
Effective Path ◽  
Grid Based

AbstractNavigation of mobile robots in a grid based environment is useful in applications like warehouse automation. The environment comprises of a number of free grid cells for navigation and remaining grid cells are occupied by obstacles and/or other mobile robots. Such obstructions impose situations of collisions and dead-end. In this work, a neural dynamics based algorithm is proposed for complete coverage of a grid based environment while addressing collision avoidance and dead-end situations. The relative heading of the mobile robot with respect to the neighbouring grid cells is considered to calculate the neural activity. Moreover, diagonal movement of the mobile robot through inter grid cells is restricted to ensure safety from the collision with obstacles and other mobile robots. The circumstances where the proposed algorithm will fail to provide completeness are also discussed along with the possible ways to overcome those situations. Simulation results are presented to show the effectiveness of the proposed algorithm for a single and multiple mobile robots. Moreover, comparative studies illustrate improvements over other algorithms on collision free effective path planning of mobile robots within a grid based environment.

A Algorithm of Path Planning Based on Multiple Mobile Robots

2013 ◽  
Vol 470 ◽  
pp. 621-624 ◽  
Author(s):  
Xiao Dong Tan ◽  
Xu Wang ◽  
Pi Wei Song
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Dynamic Environment ◽  
Grid Method ◽  
Intelligent Robot ◽  
A Algorithm ◽  
Environmental Model ◽  
Multiple Mobile Robots ◽  
Traffic Rules

The environment of automated warehouse is complex. Path collision exists conflict between intelligent robot with unknown obstacles and intelligent mobile-robot, increasing the difficulty in multiple mobile robots path planning.To solve the problem, firstly working environmental model is established with traffic rules method and the grid method. Then the whole system adopts the idea of hierarchical cooperation for dynamic local and global path planning.By simulation this method is suitable for dynamic environment with known and unknown obstacles and effectively solve the problem of path planning for multiple mobile robots in automated warehouse.

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