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Dynamic Topological Mapping with Biobotic Swarms
[article]
2015
arXiv
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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
2019
IEEE Access
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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]
2017
Springer Proceedings in Advanced Robotics
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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
2018
IEEE Transactions on robotics
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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
2008
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08
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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
2007
2007 46th IEEE Conference on Decision and Control
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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
2021
IEEE Access
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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
2019
International Journal of Advanced Computer Science and Applications
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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
2012
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
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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
2016
Robotica (Cambridge. Print)
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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
2015
2015 IEEE International Conference on Robotics and Automation (ICRA)
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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
2010
International Journal of Computer Applications
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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]
2014
Lecture Notes in Computer Science
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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
2013
International Journal of Signal and Imaging Systems Engineering
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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
2015
International Journal of Computer Applications
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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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