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Dynamic Topological Mapping with Biobotic Swarms [article]

Alireza Dirafzoon and Alper Bozkurt and Edgar Lobaton
2015 arXiv   pre-print
In this paper, we present an approach for dynamic exploration and mapping of unknown environments using a swarm of biobotic sensing agents, with a stochastic natural motion model and a leading agent (e.g  ...  The proposed robust mapping technique constructs a topological map of the environment using only encounter information from the swarm.  ...  Given this minimal sensing scenario, we aim to build a sketch of the unknown scene, which includes information about topological and geometrical features of the environment A.  ... 
arXiv:1507.03206v2 fatcat:6hhb2nwgvjd55hcy53mnvmiob4

Hybrid Stochastic Exploration using Grey Wolf Optimizer and Coordinated Multi-robot Exploration algorithms

Kamalova Albina, Suk Gyu Lee
2019 IEEE Access  
Multi-robot exploration is a search of uncertainty in restricted space seeking to build a finite map by a group of robots.  ...  It uses the Coordinated Multi-Robot Exploration and Grey Wolf Optimizer algorithms as a new method called the hybrid stochastic exploration.  ...  Some of the well-known applications are path planning, navigation, localization, communication, and sensing, that work on preconditioned maps of environments.  ... 
doi:10.1109/access.2019.2894524 fatcat:7pgbwfo74rfdhays252gri4dba

An Optimal Control Approach to Mapping GPS-Denied Environments Using a Stochastic Robotic Swarm [chapter]

Ragesh K. Ramachandran, Karthik Elamvazhuthi, Spring Berman
2017 Springer Proceedings in Advanced Robotics  
This paper presents an approach to mapping a region of interest using observations from a robotic swarm without localization.  ...  The map of the environment is incorporated into this model using a spatially-dependent indicator function that marks the presence or absence of the region of interest throughout the domain.  ...  To address these challenges, we present a method for mapping a feature of interest in an unknown environment using a swarm of robots with local sensing capabilities, no localization, and no inter-robot  ... 
doi:10.1007/978-3-319-51532-8_29 dblp:conf/isrr/RamachandranEB15 fatcat:rzgfip363nezjk5rjwxvkatwou

A Survey on Aerial Swarm Robotics

Soon-Jo Chung, Aditya Avinash Paranjape, Philip Dames, Shaojie Shen, Vijay Kumar
2018 IEEE Transactions on robotics  
The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware.  ...  Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional (3-D) space, and the dynamics of individual vehicles adds an extra layer of complexity.  ...  In the last, the goal is to build a map of the unknown or partially-known environment. A. Target Search and Tracking Target search and tracking is a canonical distributed sensing task.  ... 
doi:10.1109/tro.2018.2857475 fatcat:4blp42msbzakvmwlwyd3e57o2e

Autonomous agent behavior generation using multiobjective evolutionary optimization

Dustin J. Nowak, Gary B. Lamont
2008 Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08  
The purpose of the paper then is to explore this idea built upon our unmanned aerial vehicle (UAV) swarm model and simulation that uses autonomous self-organized concepts.  ...  To allow these behaviors to properly evolve, a multi-objective evolutionary algorithm generates a self-organized rule-based agent swarm.  ...  Acknowledgment This effort is in support of the AFIT Advanced Navigation Technology (Ant) Center.  ... 
doi:10.1145/1388969.1389007 dblp:conf/gecco/NowakL08 fatcat:h7dsb3qo6bhpfdepzbpf7yue5q

Cooperatively learning mobile agents for gradient climbing

Jongeun Choi, Songhwai Oh, Roberto Horowitz
2007 2007 46th IEEE Conference on Decision and Control  
It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map.  ...  This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing.  ...  CONCLUSIONS This paper presented a novel class of self-organizing autonomous sensing agents that form a swarm and learn through noisy cooperative measurements from neighboring agents to estimate an unknown  ... 
doi:10.1109/cdc.2007.4434061 dblp:conf/cdc/ChoiOH07 fatcat:o7cibyksknfh5ghjclgrmluiuq

Multi-Robot Space Exploration: An Augmented Arithmetic Approach

Faiza Gul, Imran Mir, Laith Abualigah, Putra Sumari
2021 IEEE Access  
The method of creating models of environments from sensor data is known as exploration. The exploration aims to make a finite map of indoor space.  ...  Path planning, routing, localization, networking, and sensing are some of the well-known technologies that deal with preconditioned maps of the ecosystems [19] .  ...  I am also interested on the use of brain signals for computer application.  ... 
doi:10.1109/access.2021.3101210 fatcat:55evp37o3vhgtbdzhler7sjxju

Swarm Robotics and Rapidly Exploring Random Graph Algorithms Applied to Environment Exploration and Path Planning

Cindy Calder´on-Arce, Rebeca Solis-Ortega
2019 International Journal of Advanced Computer Science and Applications  
We propose an efficient scheme based on a swarm robotics approach for exploring unknown environments. The initial goal is to trace a map which is later used to find optimal paths.  ...  A cellular automata approach is used for the simulation of the fist two phases. For the exploration phase, a stigmergy approach is applied in order to allow for swarm communication in a implicit way.  ...  These results are part of that project.  ... 
doi:10.14569/ijacsa.2019.0100586 fatcat:gccatntjhrac5hlofikrezi2sa

A comparison of deterministic and stochastic approaches for allocating spatially dependent tasks in micro-aerial vehicle collectives

Karthik Dantu, Spring Berman, Bryan Kate, Radhika Nagpal
2012 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems  
a combination of high error in localization, navigation, and sensing.  ...  We compare our previously developed deterministic [7] and stochastic [3] , [4] strategies for allocating tasks in robotic swarms 1 consisting of very large populations of highly resource-constrained robots  ...  ACKNOWLEDGMENT The authors gratefully acknowledge support from NSF Award CCF-0926148.  ... 
doi:10.1109/iros.2012.6386233 dblp:conf/iros/DantuBKN12 fatcat:xv4kgpj2sfgphnj43tqpaidqfi

Immune-inspired search strategies for robot swarms

G. M. Fricke, J. P. Hecker, J. L. Cannon, M. E. Moses
2016 Robotica (Cambridge. Print)  
We use a robot swarm to evaluate the effectiveness of a Lévy search strategy and map the relationship between search parameters and target configurations.  ...  Implementing search behaviors observed in T cells in a robot swarm provides an effective, adaptable, and scalable swarm robotic search strategy.  ...  The success of robot swarms searching for targets in an unknown environment depends on the adaptability and robustness of the search strategy.  ... 
doi:10.1017/s0263574716000382 fatcat:luoo77jjereireammdo6glf6bu

Optimal control of stochastic coverage strategies for robotic swarms

Karthik Elamvazhuthi, Spring Berman
2015 2015 IEEE International Conference on Robotics and Automation (ICRA)  
This paper addresses a trajectory planning and task allocation problem for a swarm of resource-constrained robots that cannot localize or communicate with each other and that exhibit stochasticity in their  ...  The planning and allocation problem can then be formulated as a PDE-constrained optimization problem, which we solve using techniques from optimal control.  ...  Stochastic approaches to the ST-MR problem for robotic swarms have been developed in which tasks are executed at random times by unidentified robots and an allocation emerges from the collective swarm  ... 
doi:10.1109/icra.2015.7139435 dblp:conf/icra/ElamvazhuthiB15 fatcat:ybeown22t5aajk57oswinflq7m

Cross-Country Path Finding using Hybrid approach of PSO and BBO

Harish Kundra, Monica Sood
2010 International Journal of Computer Applications  
This paper describes a novel approach of autonomous navigation for outdoor vehicles which includes terrain mapping, obstacle detection and avoidance, and goal seeking in cross-country using Swarm Intelligence  ...  This paper combines the strengths of both Particle Swarm optimization (PSO) for finding out the natural paths moreover keeping the obstacle detection from the satellite image, and Biogeography Based Optimization  ...  Path planning is a task to generate a safest path connecting the start and the destination in a known or unknown environment in terms of the shortest path and obstacle avoidance.  ... 
doi:10.5120/1167-1370 fatcat:k4ysslejjrdgvis7ror3efopmi

On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery [chapter]

Michael Preuß, Matthias Dehmer, Stefan Pickl, Andreas Holzinger
2014 Lecture Notes in Computer Science  
Moreover, we describe some methods from quantitative graph theory and outline a few potential research routes.  ...  In particular, the analysis is important for improving the estimation of the parameter set for the used heuristic in the field of route planning.  ...  By means of smart autonomous single agents or a swarm, these applications pursue the main objective to cover an unknown environment without any a priori information.  ... 
doi:10.1007/978-3-319-09891-3_51 fatcat:imscvvz6jjhtzjngkkgp53adsq

Maximum likelihood source localisation in wireless sensor network using particle swarm optimisation

T. Panigrahi, G. Panda, B. Majhi
2013 International Journal of Signal and Imaging Systems Engineering  
Wireless sensor networks have been proposed as a solution to environment sensing, target tracking, data collection and other applications.  ...  In literature a decentralized approach using strong antena arrays at each node or sensor arrays at different positions are used to localize the sources.  ...  A vast number of algorithms has appeared in the literature for estimating unknown signal parameters from the measured output of a sensor array [1] .  ... 
doi:10.1504/ijsise.2013.053414 fatcat:ce5f23kxszcdxlwuwn452yybca

Computational Intelligence Techniques for Wireless Sensor Network: Review

Sonal Chawla, Manju Manju, Sugandha Singh
2015 International Journal of Computer Applications  
Wireless sensors (nodes) in the network sense extract data from the various surrounding environment, sequence the sensed data locally, and then transfer the data to a base station for further processing  ...  Clustering is a technique that is used for managing energy consumption. However, clustering is NP hard optimization problem that can't be solved effectively by traditional methods.  ...  The sensing unit have at least one sensor that measures the data from its surrounding environment. Various sensing units exist according to the application deployed.  ... 
doi:10.5120/20815-3180 fatcat:ijc3now5jvdptdqcv4zaxxpkca
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