Works (6)
Updated: July 5th, 2023 15:41
2016 journal article
A framework for mapping with biobotic insect networks: From local to global maps
Robotics and Autonomous Systems, 88, 79–96.
TL;DR:
Simulation and experimental results with biologically inspired robotic platform are presented to illustrate and verify the correctness of the approach, which provides building blocks for SLAM with biobotic insects.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018
2016 journal article
Geometric Learning and Topological Inference With Biobotic Networks
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 3(1), 200–215.
author keywords: Biobotic insects; emergency response; estimation; manifold learning; mapping; topological pattern recognition
TL;DR:
This study considers agents mimicking motion behaviors of cyborg insects, known as biobots, and exploit coordinate-free local interactions among them to infer geometric and topological information about the environment, under minimal sensing and localization constraints.
(via Semantic Scholar)
open access via doi.org (publisher)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018
2014 article
Biobotic Insect Swarm based Sensor Networks for Search and Rescue
(I. Kadar, Ed.). SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXIII, Vol. 9091.
Ed(s): I. Kadar
author keywords: Insect biobots; Seach and rescue; Neural engineering; Swarm robotics; Topological mapping; Sensor networks
TL;DR:
This work has benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: August 6, 2018
2014 conference paper
Mapping of unknown environments using minimal sensing from a stochastic swarm
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3842–3849.
TL;DR:
A robust approach to obtain a topological map of an unknown environment using encounter information from a swarm of agents following a stochastic motion model via the use of tools from topological data analysis is proposed.
(via Semantic Scholar)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018
2014 conference paper
Poster abstract: Cyborg-insect networks for mapping of unknown environments
2014 acm/ieee international conference on cyber-physical systems (iccps), 216–216.
TL;DR:
This work proposes a robust approach to obtain a topological map of an unknown environment using the coordinate free sensory data obtained from these cyborg-insect networks, and takes advantage of the natural behavior of insects in order to estimate aTopological model of the environment based only on neighbor-to-neighbor interactions.
(via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018
2013 conference paper
Topological mapping of unknown environments using an unlocalized robotic swarm
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 5545–5551.
TL;DR:
This paper explores how stochastic motion models and weak encounter information can be exploited to learn topological information about an unknown environment and proposes a switching control mechanism for the motion models to extract features of complex environments in an effective way.
(via Semantic Scholar)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018
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