@inproceedings{xiong_latif_lobaton_bozkurt_sichitiu_2016, title={Characterization of RSS variability for biobot localization using 802.15.4 radios}, DOI={10.1109/wisnet.2016.7444305}, abstractNote={A cyber-physically organized swarm of insect biobots or biological robots can aid first responders in search-and-rescue scenarios after natural disasters or earthquakes by establishing an under-rubble sensor network. In such a network, the nodes are represented by the insect biobots equipped with electronic backpacks utilizing a system-on-chip. This application requires effective real-time localization of the mobile sensor nodes. Radio signal strength (RSS) is a measurement of the received signal power, and can be used in estimating the distance between two nodes, which then can help localize the biobotic sensor nodes in the future. This paper investigates RSS variability and its suitability for biobotic localization.}, booktitle={2016 ieee topical conference on wireless sensors and sensor networks (wisnet)}, author={Xiong, H. and Latif, T. and Lobaton, E. and Bozkurt, A. and Sichitiu, Mihail L.}, year={2016}, pages={1–3} }
 @inproceedings{xiong_sichitiu_2016, title={KickLoc: Simple, distributed localization for wireless sensor networks}, DOI={10.1109/mass.2016.037}, abstractNote={The emergence of location-based applications in wireless sensor network has galvanized extensive research on localization. Nonetheless, localization remains a difficult problem due to trade-offs between accuracy, energy consumption and computing resources. Searching for a solution that is sufficiently robust to handle a variety of scenarios, we propose KickLoc, which is a fully distributed solution. KickLoc takes the reliability of distance measurements into account to mitigate errors resulting from distance measurement errors, and fuses information from all neighboring nodes to provide position estimates. We evaluated the proposed algorithms both through simulations and experiments, the results are compared with other localization schemes and the Cramer-Rao lower bound (CRLB). The results show that the proposed algorithms outperform existing solutions in most of scenarios, while requiring significantly lower resources.}, booktitle={Proceedings 2016 ieee 13th international conference on mobile ad hoc and sensor systems (mass 2016)}, author={Xiong, H. and Sichitiu, Mihail L.}, year={2016}, pages={228–236} }
 @inproceedings{xiong_gong_qu_du_harfoush_2015, title={CSI-based device-free gesture detection}, booktitle={2015 12th International Conference on High-Capacity Optical Networks and Enabling/Emerging Technologies (HONET)}, author={Xiong, H. and Gong, F. Y. and Qu, L. and Du, C. L. and Harfoush, K.}, year={2015}, pages={122–126} }
 @article{bozkurt_lobaton_sichitiu_hedrick_latif_dirafzoon_whitmire_verderber_marin_xiong_et al._2014, title={Biobotic Insect Swarm based Sensor Networks for Search and Rescue}, volume={9091}, ISSN={["1996-756X"]}, url={http://dx.doi.org/10.1117/12.2053906}, DOI={10.1117/12.2053906}, abstractNote={The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have 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. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.}, journal={SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXIII}, publisher={SPIE}, author={Bozkurt, A. and Lobaton, E. and Sichitiu, Mihail L. and Hedrick, T. and Latif, T. and Dirafzoon, A. and Whitmire, E. and Verderber, A. and Marin, J. and Xiong, H. and et al.}, editor={Kadar, IvanEditor}, year={2014} }