[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row background_position=”top_left” background_repeat=”repeat” background_size=”initial”][et_pb_column type=”2_3″][et_pb_image src=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/7\/2016\/01\/Biobots.png” show_in_lightbox=”off” url_new_window=”off” use_overlay=”off” animation=”left” sticky=”off” align=”left” force_fullwidth=”off” always_center_on_mobile=”on” use_border_color=”off” border_color=”#ffffff” border_style=”solid” animation_style=”slide” animation_duration=”500ms” animation_intensity_slide=”10%” animation_direction=”left” show_bottom_space=”on”]<\/p>\n
<\/p>\n
[\/et_pb_image][\/et_pb_column][et_pb_column type=”1_3″][et_pb_text admin_label=”Description” background_layout=”light” text_orientation=”left” use_border_color=”off” border_color=”#ffffff” border_style=”solid” background_position=”top_left” background_repeat=”repeat” background_size=”initial”]<\/p>\n
Current technology falls short in offering mobile robotic agents that function effectively under complex, nonhomogenous, and under-rubble environments emerging after for example a natural disaster. Insects, on the other hand, exhibit an unmatched ability to navigate through a variety of environments via efficient locomotion. This project aims to develop algorithms for data aggregation and control of biobotic insect networks consisting of cybernetic Madagascar hissing cockroaches, called \u201cbiobots\u201d.<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row background_position=”top_left” background_repeat=”repeat” background_size=”initial”][et_pb_column type=”4_4″][et_pb_text admin_label=”Description2″ background_layout=”light” text_orientation=”left” use_border_color=”off” border_color=”#ffffff” border_style=”solid” background_position=”top_left” background_repeat=”repeat” background_size=”initial”]<\/p>\n
Our system combines biological and synthetic sensors, wireless networking, mapping and localization, and motion planning. We study the behavior and motion models of normal and biobotic insects, exploiting their natural behavior to develop algorithms and software for the estimation of geometric and topological maps of unknown environments where global localization and mapping techniques fail. Topological data about the environment is supplemented with inertial, magnetic, acoustic, and signal strength information for the localization of the biobots. Furthermore, algorithms that combine cockroaches and aerial agents are considered to explore and map larger and more complex environments. We demonstrate the feasibility and performance of our algorithms by conducting experiments on our own robotic platform (WolfBots) as well as miniature robotic insects such as the Hexbug. Field testing is performed using hissing cockroaches controlled with embedded chips.<\/p>\n
This work is done in collaboration with the iBionicS lab (NCSU), the WALAN Lab (NCSU) and the Hedrick Lab (UNC) under the support of NSF award CNS-1239243 (Aug 2012 – Dec\u00a02016).<\/p>\n
[\/et_pb_text][et_pb_text admin_label=”Resources” background_layout=”light” text_orientation=”left” use_border_color=”off” border_color=”#ffffff” border_style=”solid” background_position=”top_left” background_repeat=”repeat” background_size=”initial”]<\/p>\n
Resources<\/h3>\n\n- Biobot Behavior Analysis<\/a> – Paper:\u00a0\u201cBiobotic Motion and Behavior Analysis in Response to Directional Neurostimulation,<\/strong>\u201d ICASSP 2017<\/li>\n
- Dynamic Topological Mapping: Hexbugs Video<\/a>\u00a0– Paper: “A Framework for Mapping with Biobotic Insect Networks: From Local to Global Maps,<\/strong>” RAS Journal 2016<\/li>\n
- Dynamic Topological Mapping: Simulation Video<\/a>\u00a0– Paper: “A Framework for Mapping with Biobotic Insect Networks: From Local to Global Maps,<\/strong>”\u00a0RAS Journal 2016<\/li>\n
- Static Topological Mapping: WolfBots Video<\/a>\u00a0– Paper: \u201cMapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm<\/strong>,\u201d IROS 2014<\/li>\n
- Static Topological Mapping: Simulation Video<\/a>\u00a0– Paper: “Topological Mapping of Unknown Environments using an Unlocalized Robotic Swarm<\/strong>,”\u00a0<\/strong>IROS 2013<\/li>\n<\/ul>\n
[\/et_pb_text][et_pb_text admin_label=”Publications” use_border_color=”off” background_position=”top_left” background_repeat=”repeat” background_size=”initial” _builder_version=”3.1.1″]<\/p>\n
Publications<\/h3>\n\n- J. Cole, T. Agcayazi, T. Latif, A. Bozkurt, E. Lobaton, \u201cSpeed Estimation based on Gait Analysis for Biobotic Agents,<\/strong>\u201d IEEE Sensors Conf., 2017.<\/li>\n
- J. Cole, F. Mohammadzadeh, C. Bollinger, T. Latif, A. Bozkurt, E. Lobaton, “A Study on Motion Mode Identification for Cyborg Roaches,<\/strong>” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.<\/li>\n
- A. Dirafzoon, T. Latif, F. Gong, M. Sichitiu, A. Bozkurt, E. Lobaton, “Biobotic Motion and Behavior Analysis in Response to Directional Neurostimulation<\/strong>,” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017. [ VIDEO<\/a> ]<\/li>\n
- A. Dirafzoon, A. Bozkurt and E. Lobaton, “Geometric Learning and Topological Inference with Biobotic Networks<\/strong>,” IEEE Transactions on Signal and Information Processing over Networks,Volume PP, Issue 99, 2016.<\/li>\n
- A. Dirafzoon, A. Bozkurt and E. Lobaton, “\u201cA Framework for Mapping with Biobotic Insect Networks: From Local to Global Maps,<\/strong>” Robotics and Autonomous Systems Journal, Volume 88, pp.79-96, 2016.\u00a0[ Video 1<\/a> | Video 2<\/a> ]<\/li>\n
- T. Latif, M. Yang, E. Lobaton and A. Bozkurt, “Preliminary Statistical Assessment towards Characterization of Biobotic Contro<\/strong>l,” IEEE Engineering in Medicine and Biology Conference (EMBC), 2016.<\/li>\n
- A. Bozkurt, E. Lobaton, and M. Sichitiu, \u201cBiobotic Insect Sensor Networks for Search and Rescue<\/strong>,\u201d The Journal of the Homeland Defense and Security Information Analysis Center (HDIAC), Volume 2, Issue 2, pp.29-33, June 2015.<\/li>\n
- A. Dirafzoon, A. Bozkurt, and E. Lobaton, \u201cExploration and topological mapping with Hexbugs<\/strong>,\u201d in Proc. 14th International Conference on Information Processing in Sensor Networks (IPSN), ACM, New York, NY, 2015, pp. 406\u2013407.<\/li>\n
- A. Dirafzoon, J. Betthauser, J. Schornick, and E. Lobaton, \u201cMapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm<\/strong>,\u201d in Proc. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), Chicago, IL, 2014, pp. 3842\u20133849. [ VIDEO <\/a>]<\/li>\n
- A. Bozkurt, E. Lobaton, M. Sichitiu, T. Hedrick, T. Latif, A. Dirafzoon, E. Whitmire, A. Verderber, J. Marin, and H. Xiong, \u201cBiobotic Insect Swarm based Sensor Networks for Search and Rescue<\/strong>,\u201d in Proc. SPIE Defense, Security, and Sensing, Baltimore, MD, 2014, pp. 90911L.<\/li>\n
- A. Dirafzoon, J. Bethhauser, J. Schornick, J. Cole, A. Bozkurt, and E. Lobaton, \u201cCyborg-Insect Networks for Mapping of Unknown Environments<\/strong>,\u201d in Proc. ACM\/IEEE International Conference on Cyber-Physical Systems (ICCPS), Berlin, Germany, 2014, pp. 216\u2013216.<\/li>\n
- J. Betthauser, D. Benavides, J. Schornick, N. O\u2019Hara, J. Patel, J. Cole, and E. Lobaton, \u201cWolfBot: A Distributed Mobile Sensing Platform for Research and Education<\/strong>,\u201d Zone-1 Conference of the American Society for Engineering Education, Bridgeport, CT, 2014, pp. 1-8. [ VIDEOS<\/a> ]<\/li>\n
- A. Dirafzoon and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,<\/strong>\u201d in Proc. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan,2013, pp. 5545\u20135551. [ VIDEO <\/a>]<\/li>\n<\/ul>\n
[\/et_pb_text][et_pb_text admin_label=”News” use_border_color=”off” background_position=”top_left” background_repeat=”repeat” background_size=”initial” _builder_version=”3.15″]<\/p>\n
In the News<\/h3>\n\n- October 23, 2018 – WRAL TechWire – IoT Demo Night Wonders<\/a><\/li>\n
- November 18, 2016 \u2013 Seeker \u2013 Drones and Cyborg Roaches Team Up to Map Disaster Zones<\/a><\/li>\n
- November 17, 2016 \u2013 TechXplore \u2013 Tech would use Drones and Insect Biobots to Map Disaster Areas<\/a><\/li>\n
- July 22, 2015 \u2013 New Scientist \u2013 Cyborg Cockroach and Drone Teams can Locate Disaster Survivors<\/a><\/li>\n
- December 13, 2013 \u2013 IEEE Spectrum \u2013 Cyborg Cockroaches to the Rescue<\/a><\/li>\n
- October 18, 2013 \u2013 The Wall Street Journal \u2013 Send In the Cockroach Squad<\/a><\/li>\n
- October 16, 2013 \u2013 Gigaom \u2013 Cyborg Insects could Map Collapsed Buildings for First Responders<\/a><\/li>\n
- October 16, 2013 \u2013 NBC News \u2013 Don\u2019t Panic! These Cyborg Roaches are Trained for Emergencies<\/a><\/li>\n
- October 16, 2013 \u2013 NCSU News \u2013 Software Uses Cyborg Swarm to Map Unknown Environs<\/a><\/li>\n<\/ul>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Cyborg Insect Networks Current technology falls short in offering mobile robotic agents that function effectively under complex, nonhomogenous, and under-rubble environments emerging after for example a natural disaster. Insects, […]<\/p>\n","protected":false},"author":44,"featured_media":381,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"
\u00a0<\/p>
This project aims to develop algorithms for data aggregation and control of robotic sensor networks formed by swarms of cyborg insects (biobots). We make use a setup that combines biological and synthetic sensors, wireless networking, mapping and localization, and motion planning. This work is done in collaboration with the iBionicS lab<\/strong><\/a> (NCSU), the WALAN Lab<\/strong><\/a> (NCSU) and the Hedrick Lab<\/strong><\/a> (UNC) under the support of NSF award CNS-1239243.<\/p>\u00a0<\/p>
![\"Biobotic](\"https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/7\/2013\/04\/BioboticSwarm_500x400.png\")
<\/a><\/td>Topological Mapping of the Environment<\/strong><\/span><\/p>Fall 2012 - Present<\/p>
We aim to develop data analysis algorithms to learn topological information about an unknown environment based on data aggregated from biobotic agents moving according to probabilistic motion model of cockroaches under weak localization constraints. Tools from algebraic topology are employed to extract spatial information of the environment based on neighbor to neighbor interactions.<\/p>
Papers:<\/strong><\/p>- A. Dirafzoon, J. Betthauser, J. Schornick, D. Benavides and E. Lobaton, \"Mapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm,\" Intl. Conf. on Intelligent Robots and Systems (IROS), 2014.<\/li>
- A. Dirafzoon and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,\u201d Intl. Conf. on Intelligent Robots and Systems (IROS), 2013.<\/a><\/li><\/ul>
\u00a0<\/p>
Videos:<\/strong><\/p>
[\/et_pb_text][et_pb_text admin_label=”Publications” use_border_color=”off” background_position=”top_left” background_repeat=”repeat” background_size=”initial” _builder_version=”3.1.1″]<\/p>\n
Publications<\/h3>\n\n- J. Cole, T. Agcayazi, T. Latif, A. Bozkurt, E. Lobaton, \u201cSpeed Estimation based on Gait Analysis for Biobotic Agents,<\/strong>\u201d IEEE Sensors Conf., 2017.<\/li>\n
- J. Cole, F. Mohammadzadeh, C. Bollinger, T. Latif, A. Bozkurt, E. Lobaton, “A Study on Motion Mode Identification for Cyborg Roaches,<\/strong>” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.<\/li>\n
- A. Dirafzoon, T. Latif, F. Gong, M. Sichitiu, A. Bozkurt, E. Lobaton, “Biobotic Motion and Behavior Analysis in Response to Directional Neurostimulation<\/strong>,” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017. [ VIDEO<\/a> ]<\/li>\n
- A. Dirafzoon, A. Bozkurt and E. Lobaton, “Geometric Learning and Topological Inference with Biobotic Networks<\/strong>,” IEEE Transactions on Signal and Information Processing over Networks,Volume PP, Issue 99, 2016.<\/li>\n
- A. Dirafzoon, A. Bozkurt and E. Lobaton, “\u201cA Framework for Mapping with Biobotic Insect Networks: From Local to Global Maps,<\/strong>” Robotics and Autonomous Systems Journal, Volume 88, pp.79-96, 2016.\u00a0[ Video 1<\/a> | Video 2<\/a> ]<\/li>\n
- T. Latif, M. Yang, E. Lobaton and A. Bozkurt, “Preliminary Statistical Assessment towards Characterization of Biobotic Contro<\/strong>l,” IEEE Engineering in Medicine and Biology Conference (EMBC), 2016.<\/li>\n
- A. Bozkurt, E. Lobaton, and M. Sichitiu, \u201cBiobotic Insect Sensor Networks for Search and Rescue<\/strong>,\u201d The Journal of the Homeland Defense and Security Information Analysis Center (HDIAC), Volume 2, Issue 2, pp.29-33, June 2015.<\/li>\n
- A. Dirafzoon, A. Bozkurt, and E. Lobaton, \u201cExploration and topological mapping with Hexbugs<\/strong>,\u201d in Proc. 14th International Conference on Information Processing in Sensor Networks (IPSN), ACM, New York, NY, 2015, pp. 406\u2013407.<\/li>\n
- A. Dirafzoon, J. Betthauser, J. Schornick, and E. Lobaton, \u201cMapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm<\/strong>,\u201d in Proc. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), Chicago, IL, 2014, pp. 3842\u20133849. [ VIDEO <\/a>]<\/li>\n
- A. Bozkurt, E. Lobaton, M. Sichitiu, T. Hedrick, T. Latif, A. Dirafzoon, E. Whitmire, A. Verderber, J. Marin, and H. Xiong, \u201cBiobotic Insect Swarm based Sensor Networks for Search and Rescue<\/strong>,\u201d in Proc. SPIE Defense, Security, and Sensing, Baltimore, MD, 2014, pp. 90911L.<\/li>\n
- A. Dirafzoon, J. Bethhauser, J. Schornick, J. Cole, A. Bozkurt, and E. Lobaton, \u201cCyborg-Insect Networks for Mapping of Unknown Environments<\/strong>,\u201d in Proc. ACM\/IEEE International Conference on Cyber-Physical Systems (ICCPS), Berlin, Germany, 2014, pp. 216\u2013216.<\/li>\n
- J. Betthauser, D. Benavides, J. Schornick, N. O\u2019Hara, J. Patel, J. Cole, and E. Lobaton, \u201cWolfBot: A Distributed Mobile Sensing Platform for Research and Education<\/strong>,\u201d Zone-1 Conference of the American Society for Engineering Education, Bridgeport, CT, 2014, pp. 1-8. [ VIDEOS<\/a> ]<\/li>\n
- A. Dirafzoon and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,<\/strong>\u201d in Proc. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan,2013, pp. 5545\u20135551. [ VIDEO <\/a>]<\/li>\n<\/ul>\n
[\/et_pb_text][et_pb_text admin_label=”News” use_border_color=”off” background_position=”top_left” background_repeat=”repeat” background_size=”initial” _builder_version=”3.15″]<\/p>\n
In the News<\/h3>\n\n- October 23, 2018 – WRAL TechWire – IoT Demo Night Wonders<\/a><\/li>\n
- November 18, 2016 \u2013 Seeker \u2013 Drones and Cyborg Roaches Team Up to Map Disaster Zones<\/a><\/li>\n
- November 17, 2016 \u2013 TechXplore \u2013 Tech would use Drones and Insect Biobots to Map Disaster Areas<\/a><\/li>\n
- July 22, 2015 \u2013 New Scientist \u2013 Cyborg Cockroach and Drone Teams can Locate Disaster Survivors<\/a><\/li>\n
- December 13, 2013 \u2013 IEEE Spectrum \u2013 Cyborg Cockroaches to the Rescue<\/a><\/li>\n
- October 18, 2013 \u2013 The Wall Street Journal \u2013 Send In the Cockroach Squad<\/a><\/li>\n
- October 16, 2013 \u2013 Gigaom \u2013 Cyborg Insects could Map Collapsed Buildings for First Responders<\/a><\/li>\n
- October 16, 2013 \u2013 NBC News \u2013 Don\u2019t Panic! These Cyborg Roaches are Trained for Emergencies<\/a><\/li>\n
- October 16, 2013 \u2013 NCSU News \u2013 Software Uses Cyborg Swarm to Map Unknown Environs<\/a><\/li>\n<\/ul>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Cyborg Insect Networks Current technology falls short in offering mobile robotic agents that function effectively under complex, nonhomogenous, and under-rubble environments emerging after for example a natural disaster. Insects, […]<\/p>\n","protected":false},"author":44,"featured_media":381,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"
\u00a0<\/p>
This project aims to develop algorithms for data aggregation and control of robotic sensor networks formed by swarms of cyborg insects (biobots). We make use a setup that combines biological and synthetic sensors, wireless networking, mapping and localization, and motion planning. This work is done in collaboration with the iBionicS lab<\/strong><\/a> (NCSU), the WALAN Lab<\/strong><\/a> (NCSU) and the Hedrick Lab<\/strong><\/a> (UNC) under the support of NSF award CNS-1239243.<\/p>\u00a0<\/p>
<\/a><\/td> Topological Mapping of the Environment<\/strong><\/span><\/p>Fall 2012 - Present<\/p>
We aim to develop data analysis algorithms to learn topological information about an unknown environment based on data aggregated from biobotic agents moving according to probabilistic motion model of cockroaches under weak localization constraints. Tools from algebraic topology are employed to extract spatial information of the environment based on neighbor to neighbor interactions.<\/p>
Papers:<\/strong><\/p>- A. Dirafzoon, J. Betthauser, J. Schornick, D. Benavides and E. Lobaton, \"Mapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm,\" Intl. Conf. on Intelligent Robots and Systems (IROS), 2014.<\/li>
- A. Dirafzoon and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,\u201d Intl. Conf. on Intelligent Robots and Systems (IROS), 2013.<\/a><\/li><\/ul>
\u00a0<\/p>
Videos:<\/strong><\/p>
[\/et_pb_text][et_pb_text admin_label=”News” use_border_color=”off” background_position=”top_left” background_repeat=”repeat” background_size=”initial” _builder_version=”3.15″]<\/p>\n
In the News<\/h3>\n\n- October 23, 2018 – WRAL TechWire – IoT Demo Night Wonders<\/a><\/li>\n
- November 18, 2016 \u2013 Seeker \u2013 Drones and Cyborg Roaches Team Up to Map Disaster Zones<\/a><\/li>\n
- November 17, 2016 \u2013 TechXplore \u2013 Tech would use Drones and Insect Biobots to Map Disaster Areas<\/a><\/li>\n
- July 22, 2015 \u2013 New Scientist \u2013 Cyborg Cockroach and Drone Teams can Locate Disaster Survivors<\/a><\/li>\n
- December 13, 2013 \u2013 IEEE Spectrum \u2013 Cyborg Cockroaches to the Rescue<\/a><\/li>\n
- October 18, 2013 \u2013 The Wall Street Journal \u2013 Send In the Cockroach Squad<\/a><\/li>\n
- October 16, 2013 \u2013 Gigaom \u2013 Cyborg Insects could Map Collapsed Buildings for First Responders<\/a><\/li>\n
- October 16, 2013 \u2013 NBC News \u2013 Don\u2019t Panic! These Cyborg Roaches are Trained for Emergencies<\/a><\/li>\n
- October 16, 2013 \u2013 NCSU News \u2013 Software Uses Cyborg Swarm to Map Unknown Environs<\/a><\/li>\n<\/ul>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Cyborg Insect Networks Current technology falls short in offering mobile robotic agents that function effectively under complex, nonhomogenous, and under-rubble environments emerging after for example a natural disaster. Insects, […]<\/p>\n","protected":false},"author":44,"featured_media":381,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"
\u00a0<\/p>
This project aims to develop algorithms for data aggregation and control of robotic sensor networks formed by swarms of cyborg insects (biobots). We make use a setup that combines biological and synthetic sensors, wireless networking, mapping and localization, and motion planning. This work is done in collaboration with the iBionicS lab<\/strong><\/a> (NCSU), the WALAN Lab<\/strong><\/a> (NCSU) and the Hedrick Lab<\/strong><\/a> (UNC) under the support of NSF award CNS-1239243.<\/p>\u00a0<\/p>
<\/a><\/td> Topological Mapping of the Environment<\/strong><\/span><\/p>Fall 2012 - Present<\/p>
We aim to develop data analysis algorithms to learn topological information about an unknown environment based on data aggregated from biobotic agents moving according to probabilistic motion model of cockroaches under weak localization constraints. Tools from algebraic topology are employed to extract spatial information of the environment based on neighbor to neighbor interactions.<\/p>
Papers:<\/strong><\/p>- A. Dirafzoon, J. Betthauser, J. Schornick, D. Benavides and E. Lobaton, \"Mapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm,\" Intl. Conf. on Intelligent Robots and Systems (IROS), 2014.<\/li>
- A. Dirafzoon and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,\u201d Intl. Conf. on Intelligent Robots and Systems (IROS), 2013.<\/a><\/li><\/ul>
\u00a0<\/p>
Videos:<\/strong><\/p>
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Cyborg Insect Networks Current technology falls short in offering mobile robotic agents that function effectively under complex, nonhomogenous, and under-rubble environments emerging after for example a natural disaster. Insects, […]<\/p>\n","protected":false},"author":44,"featured_media":381,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"
\u00a0<\/p>
This project aims to develop algorithms for data aggregation and control of robotic sensor networks formed by swarms of cyborg insects (biobots). We make use a setup that combines biological and synthetic sensors, wireless networking, mapping and localization, and motion planning. This work is done in collaboration with the iBionicS lab<\/strong><\/a> (NCSU), the WALAN Lab<\/strong><\/a> (NCSU) and the Hedrick Lab<\/strong><\/a> (UNC) under the support of NSF award CNS-1239243.<\/p> \u00a0<\/p> Topological Mapping of the Environment<\/strong><\/span><\/p> Fall 2012 - Present<\/p> We aim to develop data analysis algorithms to learn topological information about an unknown environment based on data aggregated from biobotic agents moving according to probabilistic motion model of cockroaches under weak localization constraints. Tools from algebraic topology are employed to extract spatial information of the environment based on neighbor to neighbor interactions.<\/p> Papers:<\/strong><\/p> \u00a0<\/p> Videos:<\/strong><\/p><\/a><\/td>