Swarm Behavior of Omni-Directional Mobile Robots using only Local Information

Author(s):  
Akimasa OTSUKA ◽  
Fusaomi NAGATA
2013 ◽  
Vol 2013 ◽  
pp. 1-15
Author(s):  
Zhenqiang Mi ◽  
Yang Yang ◽  
Jiajia Sun

Dispersion of mobile robots in a certain formation is prerequisite in many applications; one of the most important issues during the entire process is to maintain the interagent connections, as well as to restore them whenever they were broken. We investigate the aforementioned problem in this work by designing a holistic connectivity controller (HCC) to regulate and restore the interagent connections during the dispersion of the mobile network. HCC consists of two core structures. Firstly, to illustrate the multirobot dispersion, we adopt the distributed link removal algorithm (DLRA), which is able to remove redundant links in the multirobot network to facilitate the dispersion and only requires local information of no more than two-hop neighbors. Secondly, the proposed approach is extended to the problem of connectivity restoration with consideration of simultaneous failure of multiple agents. A connectivity restoration strategy is proposed, and then the recoverability of network connectivity is investigated. The proposed HCC has also integrated motion controller to regulate the movement of the mobile robots, so that interrobot collisions can be effectively avoided. Theoretical analysis and computer simulations have confirmed the efficiency and scalability of the proposed schemes.


2021 ◽  
Vol 7 ◽  
pp. e626
Author(s):  
Yehia A. Soliman ◽  
Sarah N. Abdulkader ◽  
Taha M. Mohamed

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.


Author(s):  
Saurabh Sarkar ◽  
Ernest L. Hall ◽  
Manish Kumar

This paper describes an approach that uses support vector machines (SVM) for path planning of mobile robots. The algorithm generates a collision free path for mobile robots running between two tracks or moving towards a known way point. This approach can negotiate tracks and avoid obstacles which may be initially unknown but are later perceived by the robot, and hence is suitable for use with onboard sensors which provides local information. The approach involves dividing the whole terrain into two different classes, classifying any new point obtained from sensors into either of the classes, and generating a track between both the classes as a path of the robot. SVM generates a non-linear class boundary on the principle of maximizing the margin. The boundary generated by this method is smooth, free of obstacles, and safe for a robot to navigate. The paper presents various case studies and simulation results. Future possibility to integrate this technique with other path planning techniques is also discussed.


2017 ◽  
Vol 8 (2) ◽  
pp. 19-40
Author(s):  
Gregory A Bock ◽  
Ryan T Hendrickson ◽  
Jared Allen Lamkin ◽  
Brittany Dhall ◽  
Jing Wang ◽  
...  

In this paper, we present the experimental testing results of distributed cooperative control algorithms for multiple mobile robots with limited sensing/communication capacity and kinematic constraints. Rendezvous and formation control problems are considered, respectively. To deal with the inherent kinematic constraints with robot model, the input/output linearization via feedback is used to convert the nonlinear robot model into a linear one, and then the distributed cooperative control algorithms are designed via local information exchange among robots. Extensive experiments using Quanser's QBot2 mobile robot platforms are conducted to validate the effectiveness of the proposed distributed cooperative control algorithms. Specifically, the robot's onboard Kinect vision sensor is applied to solve the localization problem, and the information exchange is done through an ad-hoc peer-to-peer wireless TCP/IP connection among neighboring robots. Collision avoidance problem is also addressed based on the utilization of fuzzy logic rules.


Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6270
Author(s):  
Hyejeong Ryu

This paper describes a graph search-based exploration method. Segmented frontier nodes and their relative transformations constitute a frontier-graph structure. Frontier detection and segmentation are performed using local grid maps of adjacent nodes. The proposed frontier-graph structure can systematically manage local information according to the exploration state and overcome the problem caused by updating a single global grid map. The robot selects the next target using breadth-first search (BFS) exploration of the frontier-graph. The BFS exploration is improved to generate an efficient loop-closing sequence between adjacent nodes. We verify that our BFS-based exploration method can gradually extend the frontier-graph structure and efficiently map the entire environment, regardless of the starting position.


2020 ◽  
pp. 743-764
Author(s):  
Gregory A Bock ◽  
Ryan T Hendrickson ◽  
Jared Allen Lamkin ◽  
Brittany Dhall ◽  
Jing Wang ◽  
...  

In this paper, we present the experimental testing results of distributed cooperative control algorithms for multiple mobile robots with limited sensing/communication capacity and kinematic constraints. Rendezvous and formation control problems are considered, respectively. To deal with the inherent kinematic constraints with robot model, the input/output linearization via feedback is used to convert the nonlinear robot model into a linear one, and then the distributed cooperative control algorithms are designed via local information exchange among robots. Extensive experiments using Quanser's QBot2 mobile robot platforms are conducted to validate the effectiveness of the proposed distributed cooperative control algorithms. Specifically, the robot's onboard Kinect vision sensor is applied to solve the localization problem, and the information exchange is done through an ad-hoc peer-to-peer wireless TCP/IP connection among neighboring robots. Collision avoidance problem is also addressed based on the utilization of fuzzy logic rules.


2013 ◽  
Vol 664 ◽  
pp. 891-896 ◽  
Author(s):  
Marek Masár ◽  
Ivana Budinská

An embedded particle swarm optimization (PSO) technique combined with virtual pheromones deposition and rules for artificial bird flocking is proposed to handle an area coverage problem using a swarm of mobile robots. A simulation tool VERA that was developed to simulate a swarm behavior of a group of mobile agents is described. Results of simulation experiments and tests on Lego robots that prove the concept are presented. Results are discussed and future development is suggested in the end of the paper.


Author(s):  
Nicolas Poirel ◽  
Claire Sara Krakowski ◽  
Sabrina Sayah ◽  
Arlette Pineau ◽  
Olivier Houdé ◽  
...  

The visual environment consists of global structures (e.g., a forest) made up of local parts (e.g., trees). When compound stimuli are presented (e.g., large global letters composed of arrangements of small local letters), the global unattended information slows responses to local targets. Using a negative priming paradigm, we investigated whether inhibition is required to process hierarchical stimuli when information at the local level is in conflict with the one at the global level. The results show that when local and global information is in conflict, global information must be inhibited to process local information, but that the reverse is not true. This finding has potential direct implications for brain models of visual recognition, by suggesting that when local information is conflicting with global information, inhibitory control reduces feedback activity from global information (e.g., inhibits the forest) which allows the visual system to process local information (e.g., to focus attention on a particular tree).


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