Research

Flight lab

A powerful platform for research


Flexible

The Crazyflie is the ideal tool for research in areas such as control algorithms, swarms, path finding, agriculture or failure recovery. The platform is designed to be as flexible and versatile as possible to enable the user to explore the area of interest.

Extendable

Add new sensors or other hardware to support your needs; the expansion port supports a variety of interfaces and there is plenty of power in the processors for you to use. If you need more lifting capacity, use the BigQuad deck and move your application to a bigger frame, while still being able to develop it in the comfort of your lab.

Tools

The Crazyflie can be controlled from a number of programming languages and also integrates with tools and frameworks such as ROS or ZeroMQ. It works well with standard development tools to make your work a breeze.

Open source

The entire firmware is open for you to change, you will never be locked in by limited APIs or closed software. Never.

Review our YouTube playlist for a collection of videos showing the Crazyflie being used for research.

For guest blog posts from researchers, and other research-related blog posts, check out the research category on our blog.

Publications


[1] Reliable Digital Forensics in the Air: Exploring an RF-Based Drone Identification System. Zhengxiong Li, Baicheng Chen, Xingyu Chen, Chenhan Xu, Yuyang Chen, Feng Lin, Changzhi Li, Karthik Dantu, Kui Ren, and Wenyao Xu. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., jul 2022. URL, DOI.
[2] Safe and Robust Observer-Controller Synthesis using Control Barrier Functions. Devansh R. Agrawal and Dimitra Panagou. IEEE Control Systems Letters, 2022. DOI.
[3] Dynamic Time Slot Allocation Algorithm for Quadcopter Swarms. Sharif Azem, Anam Tahir, and Heinz Koeppl. In 2022 IEEE 19th Annual Consumer Communications Networking Conference (CCNC). 2022. DOI.
[4] SplitFlyer Air: A Modular Quadcopter That Disassembles Into Two Bicopters Mid-Air. Songnan Bai and Pakpong Chirarattananon. IEEE/ASME Transactions on Mechatronics, 2022. DOI.
[5] A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight. Songnan Bai, Qingning He, and Pakpong Chirarattananon. Science Robotics, 2022. Video, Eprint, DOI.
[6] Cooperative Modular Single Actuator Monocopters Capable of Controlled Passive Separation. Xinyu Cai, Shane Kyi Hla Win, Luke Soe Thura Win, Danial Sufiyan, and Shaohui Foong. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[7] Passive Wall Tracking for a Rotorcraft With Tilted and Ducted Propellers Using Proximity Effects. Runze Ding, Yi-Hsuan Hsiao, Huaiyuan Jia, Songnan Bai, and Pakpong Chirarattananon. IEEE Robotics and Automation Letters, 2022. DOI.
[8] Passive Wall Tracking for a Rotorcraft With Tilted and Ducted Propellers Using Proximity Effects. Runze Ding, Yi-Hsuan Hsiao, Huaiyuan Jia, Songnan Bai, and Pakpong Chirarattananon. IEEE Robotics and Automation Letters, 2022. Video, DOI.
[9] Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation. Chiara Ercolani, Lixuan Tang, Ankita Arun Humne, and Alcherio Martinoli. IEEE Robotics and Automation Letters, 2022. DOI.
[10] Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation. Chiara Ercolani, Lixuan Tang, Ankita Arun Humne, and Alcherio Martinoli. IEEE Robotics and Automation Letters, 2022. DOI.
[11] KoopNet: Joint Learning of Koopman Bilinear Models and Function Dictionaries with Application to Quadrotor Trajectory Tracking. Carl Folkestad, Skylar X. Wei, and Joel W. Burdick. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[12] Event-Triggered Tracking Control Scheme for Quadrotors with External Disturbances: Theory and Validations. Pengcheng Gao, Gang Wang, Yunfeng Ji, Qingdu Li, Jianwei Zhang, Yantao Shen, and Peng Li. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[13] Hilding Gunnarsson and Adam Asbrink. Intelligent drone swarms: motion planning and safe collision avoidance control of autonomous drone swarms. Master’s thesis, Linkoeping University, 2022. Eprint.
[14] Aggressive maneuvering of a quadcopter via differential flatness-based fuzzy controllers: From tuning to experiments. Cagri Guzay and Tufan Kumbasar. Applied Soft Computing, 2022.
[15] Optimal Inverted Landing in a Small Aerial Robot with Varied Approach Velocities and Landing Gear Designs. Bryan Habas, Bader AlAttar, Brian Davis, Jack W. Langelaan, and Bo Cheng. In 2022 International Conference on Robotics and Automation (ICRA). 2022. Video, ArXiv, DOI.
[16] Online-Bahnplanung für mehrere Flugroboter in veränderlicher Umgebung mithilfe der Kurvenflussmethode. Marcel Huptych. Dissertation, 2022. URL.
[17] A Quadrotor With a Passively Reconfigurable Airframe for Hybrid Terrestrial Locomotion. Huaiyuan Jia, Songnan Bai, Runze Ding, Jing Shu, Yanlin Deng, Bee Luan Khoo, and Pakpong Chirarattananon. IEEE/ASME Transactions on Mechatronics, 2022. Video, DOI.
[18] Collision Avoidance for Multiple Quadrotors Using Elastic Safety Clearance Based Model Predictive Control. Tao Jin, Xinghu Wang, Haibo Ji, Jian Di, and Han Yan. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[19] MICRO AND MACRO QUADCOPTER DRONES FOR INDOOR MAPPING TO SUPPORT DISASTER MANAGEMENT. S Karam, F Nex, O Karlsson, J Rydell, E Bilock, M Tulldahl, M Holmberg, and N Kerle. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022. Eprint.
[20] Monocular vision-based time-to-collision estimation for small drones by domain adaptation of simulated images. Minwoo Kim, Pawel Ladosz, and Hyondong Oh. Expert Systems with Applications, 2022. URL, DOI.
[21] Nathan Owen Lambert. Synergy of Prediction and Control in Model-based Reinforcement Learning. PhD thesis, University of California, Berkeley, 2022. Eprint.
[22] Flying ant robot for chemical trail detection and localization. Patrick P. Neumann, Paul Hirschberger, and Matthias Bartholmai. Materials Today: Proceedings, 2022. URL, DOI.
[23] Quadrotor Formation Control via Terminal Sliding Mode Approach: Theory and Experiment Results. Ngoc Phi Nguyen, Daewon Park, Dao N. Ngoc, Nguyen Xuan-Mung, Tuan Tu Huynh, Tan N. Nguyen, and Sung Kyung Hong. Drones, 2022. URL, DOI.
[24] Towards a Multi-Pixel Time-of-Flight Indoor Navigation System for Nano-Drone Applications. Vlad Niculescu, Hanna Meuller, Iman Ostovar, Tommaso Polonelli, Michele Magno, and Luca Benini. In 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2022. DOI.
[25] Energy-efficient, Precise UWB-based 3-D Localization of Sensor Nodes with a Nano-UAV. Vlad Niculescu, Daniele Palossi, Michele Magno, and Luca Benini. IEEE Internet of Things Journal, 2022. DOI.
[26] An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System. Diana A. Olejnik, Sunyi Wang, Julien Dupeyroux, Stein Stroobants, Matej Karasek, Christophe De Wagter, and Guido de Croon. In 2022 International Conference on Robotics and Automation (ICRA). 2022. ArXiv, DOI.
[27] Nearest-Neighbor-based Collision Avoidance for Quadrotors via Reinforcement Learning. Ramzi Ourari, Kai Cui, Ahmed Elshamanhory, and Heinz Koeppl. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[28] A Bimodal Rolling-Flying Robot for Micro Level Inspection of Flat and Inclined Surfaces. Miguel Pimentel and Meysam Basiri. IEEE Robotics and Automation Letters, 2022. DOI.
[29] Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU. Nicholas Polosky, Tyler Gwin, Sean Furman, Parth Barhanpurkar, and Jithin Jagannath. In 2022 IEEE 19th Annual Consumer Communications Networking Conference (CCNC). 2022. Video, DOI.
[30] Ultra-Wideband Swarm Ranging Protocol for Dynamic and Dense Networks. Feng Shan, Haodong Huo, Jiaxin Zeng, Zengbao Li, Weiwei Wu, and Junzhou Luo. IEEE/ACM Transactions on Networking, 2022. Eprint, DOI.
[31] Monocular Depth Estimation for Light-Weight Real-Time Obstacle Avoidance. Niels Sombekke. Bachelor Thesis, 2022. Eprint.
[32] Distributed Predictive Drone Swarms in Cluttered Environments. Enrica Soria, Fabrizio Schiano, and Dario Floreano. IEEE Robotics and Automation Letters, 2022. Video, DOI.
[33] Modified Artificial Potential Field for the Path Planning of Aircraft Swarms in Three-Dimensional Environments. Rafael Monteiro Jorge Alves Souza, Gabriela Vieira Lima, Aniel Silva Morais, Luís Cláudio Oliveira-Lopes, Daniel Costa Ramos, and Fernando Lessa Tofoli. Sensors, 2022. URL, DOI.
[34] A Fast and Efficient Attitude Control Algorithm of a Tilt-Rotor Aerial Platform Using Inputs Redundancies. Yao Su, Lecheng Ruan, Pengkang Yu, Chen-Huan Pi, Matthew J. Gerber, and Tsu-Chin Tsao. IEEE Robotics and Automation Letters, 2022. DOI.
[35] Formation-containment tracking and scaling for multiple quadcopters with an application to choke-point navigation. Yu-Hsiang Su and Alexander Lanzon. In 2022 International Conference on Robotics and Automation (ICRA). 2022. ArXiv, DOI.
[36] Watch and Learn: Learning to control feedback linearizable systems from expert demonstrations. Alimzhan Sultangazin, Luigi Pannocchi, Lucas Fraile, and Paulo Tabuada. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[37] Safe multi-agent motion planning via filtered reinforcement learning. Abraham P. Vinod, Sleiman Safaoui, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, and Stefano Di Cairano. In 2022 International Conference on Robotics and Automation (ICRA). 2022. DOI.
[38] PogoDrone: Design, Model, and Control of a Jumping Quadrotor. Brian Zhu, Jiawei Xu, Andrew Charway, and David Saldaña. In 2022 International Conference on Robotics and Automation (ICRA). 2022. Video, ArXiv, DOI.
[39] A bio-mimetic miniature drone for real-time audio based short-range tracking. Roei Zigelman, Ofri Eitan, Omer Mazar, Anthony Weiss, and Yossi Yovel. PLoS computational biology, 2022.
[40] Cooperative Sensor-based Selective Graph Exploration Strategy for a Team of Quadrotors. Jinho Kim, Charles D. Eggleton, Stephen A. Wilkerson, and S. Andrew Gadsden. Journal of Intelligent and Robotic Systems: Theory and Applications, oct 2021. URL, DOI.
[41] A Computationally Efficient Moving Horizon Estimator for Ultra-Wideband Localization on Small Quadrotors. Sven Pfeiffer, Christophe De Wagter, and Guido C.H.E.De Croon. IEEE Robotics and Automation Letters, oct 2021. DOI.
[42] Nullspace-based control allocation of overactuated UAV platforms. Yao Su, Pengkang Yu, Matthew J. Gerber, Lecheng Ruan, and Tsu Chin Tsao. IEEE Robotics and Automation Letters, oct 2021. DOI.
[43] An Over-Actuated Multi-Rotor Aerial Vehicle with Unconstrained Attitude Angles and High Thrust Efficiencies. Pengkang Yu, Yao Su, Matthew J. Gerber, Lecheng Ruan, and Tsu Chin Tsao. IEEE Robotics and Automation Letters, oct 2021. DOI.
[44] Non-Prehensile Manipulation of Cuboid Objects Using a Catenary Robot. Gustavo A. Cardona, Diego S. D’Antonio, Cristian-Ioan Vasile, and David Saldaña. IROS 2021, aug 2021. ArXiv.
[45] SwarmPlay: Interactive tic-tac-toe board game with swarm of nano-UAVs driven by reinforcement learning. Ekaterina Karmanova, Valerii Serpiva, Stepan Perminov, Aleksey Fedoseev, and Dzmitry Tsetserukou. 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021, aug 2021. DOI.
[46] UWB-based Multiple UAV Control System for Indoor Ground Vehicle Tracking. Joohyun Lee, Jiseon Moon, and Sunwoo Kim. 2021 IEEE VTS 17th Asia Pacific Wireless Communications Symposium (APWCS), aug 2021. URL, DOI.
[47] Evaluating distances in tactile human-drone interaction. Marc Lieser, Ulrich Schwanecke, and Jorg Berdux. 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021, aug 2021. DOI.
[48] Use of a MEMS Differential Pressure Sensor to Detect Ground, Ceiling, and Walls on Small Quadrotors. Victoria Britcher and Sarah Bergbreiter. IEEE Robotics and Automation Letters, jul 2021. DOI.
[49] Varying-coefficient Based Distributed Formation Control of Multiple UAVs. Zhang Hepeng, Di Jian, Yan Han, Wang Xinghu, and Ji Haibo. 2021 40th Chinese Control Conference (CCC), jul 2021. URL, DOI.
[50] Decentralized formation tracking and disturbance suppression for collaborative UAVs transportation. Sijie Hu, Xizhen Zhao, Yi Ren, and Dabo Xu. 2021 40th Chinese Control Conference (CCC), jul 2021. URL, DOI.
[51] Collision-Free Trajectory Generation for Multiple UAVs with Sensing Constraints. Ruocheng Li, Qingkai Yang, Weipeng Zhao, and Hao Fang. 2021 40th Chinese Control Conference (CCC), jul 2021. URL, DOI.
[52] Comparative Validation Study on Bioinspired Morphology-Adaptation Flight Performance of a Morphing Quad-Rotor. Na Zhao, Weixin Yang, Cong Peng, Gang Wang, and Yantao Shen. IEEE Robotics and Automation Letters, jul 2021. URL, DOI.
[53] Invariant Set Distributed Explicit Reference Governors for Provably Safe On-Board Control of Nano-Quadrotor Swarms. Bryan Convens, Kelly Merckaert, Bram Vanderborght, and Marco M. Nicotra. Frontiers in Robotics and AI, jun 2021. URL, DOI.
[54] Automated Tuning of End-to-end Neural Flight Controllers for Autonomous Nano-drones. Vlad Niculescu, Lorenzo Lamberti, Daniele Palossi, and Luca Benini. 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021, jun 2021. DOI.
[55] SwarmPaint: Human-Swarm Interaction for Trajectory Generation and Formation Control by DNN-based Gesture Interface. Valerii Serpiva, Ekaterina Karmanova, Aleksey Fedoseev, Stepan Perminov, and Dzmitry Tsetserukou. 2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021, jun 2021. DOI.
[56] Sum of Square based Event-triggered Control of Nano-quadrotor in Presence of Packet Dropouts. Padmini Singh, Sandeep Gupta, Laxmidhar Behera, and Nishchal K. Verma. 2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021, jun 2021. DOI.
[57] Learning near-optimal broadcasting intervals in decentralized multi-agent systems using online least-square policy iteration. Ivana Palunko, Domagoj Tolić, and Vicko Prkačin. IET Control Theory and Applications, may 2021. URL, Video, DOI.
[58] Predictive control of aerial swarms in cluttered environments. Enrica Soria, Fabrizio Schiano, and Dario Floreano. Nature Machine Intelligence, may 2021. URL, Video, DOI.
[59] DroneTrap: Drone catching in midair by soft robotic hand with color-based force detection and hand gesture recognition. Aleksey Fedoseev, Valerii Serpiva, Ekaterina Karmanova, Miguel Altamirano Cabrera, Vladimir Shirokun, Iakov Vasilev, Stanislav Savushkin, and Dzmitry Tsetserukou. 2021 IEEE 4th International Conference on Soft Robotics, RoboSoft 2021, apr 2021. DOI.
[60] Signal-Based Self-Organization of a Chain of UAVs for Subterranean Exploration. Pierre Laclau, Vladislav Tempez, Franck Ruffier, Enrico Natalizio, and Jean Baptiste Mouret. Frontiers in Robotics and AI, apr 2021. ArXiv, Video, DOI.
[61] Learning-Based Bias Correction for Time Difference of Arrival Ultra-Wideband Localization of Resource-Constrained Mobile Robots. Wenda Zhao, Jacopo Panerati, and Angela P. Schoellig. IEEE Robotics and Automation Letters, apr 2021. ArXiv, Blog, DOI.
[62] Hierarchical task assignment and path finding with limited communication for robot swarms. Dario Albani, Wolfgang Hönig, Daniele Nardi, Nora Ayanian, and Vito Trianni. Applied Sciences (Switzerland), mar 2021. URL, URL, DOI.
[63] Online Flocking Control of UAVs with Mean-Field Approximation. Malintha Fernando. In IEEE International Conference on Robotics and Automation (ICRA). mar 2021. ArXiv, DOI.
[64] Fully Onboard AI-powered Human-Drone Pose Estimation on Ultra-low Power Autonomous Flying Nano-UAVs. Daniele Palossi, Nicky Zimmerman, Alessio Burrello, Francesco Conti, Hanna Muller, Luca Maria Gambardella, Luca Benini, Alessandro Giusti, and Jerome Guzzi. IEEE Internet of Things Journal, mar 2021. ArXiv, DOI.
[65] Controlling Draft Interactions Between Quadcopter Unmanned Aerial Vehicles with Physics-aware Modeling. Ion Matei, Chen Zeng, Souma Chowdhury, Rahul Rai, and Johan de Kleer. Journal of Intelligent and Robotic Systems: Theory and Applications, jan 2021. DOI.
[66] A few lessons learned in reinforcement learning for quadcopter attitude control. Nicola Bernini, Mikhail Bessa, Rémi Delmas, Arthur Gold, Eric Goubault, Romain Pennec, Sylvie Putot, and François Sillion. HSCC 2021 - Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (part of CPS-IoT Week), 2021. DOI.
[67] Tiny Robot Learning ( tinyRL ) for Source Seeking on a Nano Quadcopter. Bardienus P Duisterhof, Colby R Banbury, and William Fu. In IEEE International Conference on Robotics and Automation (ICRA). 2021. URL.
[68] Bardienus P. Duisterhof, Shushuai Li, Javier Burgués, Vijay Janapa Reddi, and Guido C. H. E. de Croon. Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments. 2021. ArXiv, Blog.
[69] Adaptive Speed Collision Avoidance For Dynamic Environments. Sourav Dutta, Tuan Tran, Banafsheh Rekabdar, and Chinwe Ekenna. 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021. URL, DOI.
[70] Toward battery-free flight: Duty cycled recharging of small drones. Nishant Elkunchwar, Suvesha Chandrasekaran, Vikram Iyer, and Sawyer B Fuller. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.
[71] Continuous-time Gaussian Process Trajectory Generation for Multi-robot Formation via Probabilistic Inference. Shuang Guo, Bo Liu, Shen Zhang, Jifeng Guo, and Changhong Wang. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021. Video, ArXiv.
[72] E2Coop: Energy Efficient and Cooperative Obstacle Detection and Avoidance for UAV Swarms. Shuangyao Huang, Haibo Zhang, and Zhiyi Huang. In Proceedings of the International Conference on Automated Planning and Scheduling. 2021. ArXiv.
[73] Real-time path planning in dynamic environments for unmanned aerial vehicles using the curve-shortening flow method. Marcel Huptych and Sascha Röck. International Journal of Advanced Robotic Systems, 2021. URL, DOI.
[74] Cooperative Sensor-based Selective Graph Exploration Strategy for a Team of Quadrotors. Jinho Kim, Charles D Eggleton, Stephen A Wilkerson, and S Andrew Gadsden. Journal of Intelligent & Robotic Systems, 2021.
[75] Inclined Quadrotor Landing using Deep Reinforcement Learning. Jacob E Kooi and Robert Babuska. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021. Video, ArXiv.
[76] Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation. Srivatsan Krishnan, Behzad Boroujerdian, William Fu, Aleksandra Faust, and Vijay Janapa Reddi. Machine Learning, 2021. Eprint.
[77] Scalable and Robust Algorithms for Task-Based Coordination From High-Level Specifications (ScRATCHeS). Kevin Leahy, Zachary Serlin, Cristian-Ioan Vasile, Andrew Schoer, Austin M. Jones, Roberto Tron, and Calin Belta. IEEE Transactions on Robotics, 2021. DOI.
[78] Target-visible Polynomial Trajectory Generation within an MAV Team. Yunwoo Lee, Jungwon Park, Boseong Jeon, and H Jin Kim. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021. Video.
[79] A Scalable Distributed Collision Avoidance Scheme for Multi-agent UAV systems. Bjorn Lindqvist, Pantelis Sopasakis, and George Nikolakopoulos. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021. Video, ArXiv.
[80] Trust your supervisor: quadrotor obstacle avoidance using controlled invariant sets. Luigi Pannocchi, Tzanis Anevlavis, and Paulo Tabuada. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.
[81] A Computationally Efficient Moving Horizon Estimator for Ultra-Wideband Localization on Small Quadrotors. Sven Pfeiffer, Christophe de Wagter, and Guido C.H.E. de Croon. IEEE Robotics and Automation Letters, 2021. DOI.
[82] An Event-Triggered Distributed Control Architecture for Scheduling Information Exchange in Networked Multiagent Systems. Stefan Ristevski, Tansel Yucelen, and Jonathan A. Muse. IEEE Transactions on Control Systems Technology, 2021. DOI.
[83] Neural tree expansion for multi-robot planning in non-cooperative environments. Benjamin Riviere, Wolfgang Hoenig, Matthew Anderson, and Soon-Jo Chung. IEEE Robotics and Automation Letters, 2021. Video, ArXiv.
[84] Valerii Serpiva, Ekaterina Karmanova, Aleksey Fedoseev, Stepan Perminov, and Dzmitry Tsetserukou. Dronepaint: swarm light painting with dnn-based gesture recognition. In ACM SIGGRAPH 2021 Emerging Technologies, pages 1–4. 2021. ArXiv.
[85] Deep reinforcement learning based aggressive flight trajectory tracker. Omar Shadeed, Mehmet Hasanzade, and Emre Koyuncu. AIAA Scitech 2021 Forum, 2021. DOI.
[86] Ultra-Wideband Swarm Ranging. Feng Shan, Jiaxin Zeng, Zengbao Li, Junzhou Luo, and Weiwei Wu. Proceedings - IEEE Conference on Computer Communications, 2021. Video, DOI.
[87] Lighthouse Positioning System: Dataset, Accuracy, and Precision for UAV Research. Arnaud Taffanel, Barbara Rousselot, Jonas Danielsson, Kimberly McGuire, Kristoffer Richardsson, Marcus Eliasson, Tobias Antonsson, and Wolfgang Hönig. ICRA 2021 Swarm workshop, 2021. ArXiv.
[88] micROS. BT: An Event-Driven Behavior Tree Framework for Swarm Robots. Yunlong Wu, Jinghua Li, Huadong Dai, Xiaodong Yi, Yanzhen Wang, and Xuejun Yang. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.
[89] GTO-MPC Based Target Chasing using a Quadrotor in Cluttered Environments. Lele Xi, Xinyi Wang, Lei Jiao, Shupeng Lai, Zhihong Peng, and Ben M. Chen. IEEE Transactions on Industrial Electronics, 2021. DOI.
[90] Application of a distributed control approach to an aerial swarm with a misbehaving vehicle. Emre Yildirim, Tansel Yucelen, and Stefan Ristevski. In AIAA Scitech 2021 Forum. American Institute of Aeronautics and Astronautics Inc, AIAA, 2021. URL, DOI.
[91] A bio-hybrid odor-guided autonomous palm-sized air vehicle. Melanie J. Anderson, Joseph G. Sullivan, Timothy K. Horiuchi, Sawyer B. Fuller, and Thomas L. Daniel. Bioinspiration and Biomimetics, dec 2020. Video, URL, DOI.
[92] Influence of the ground, ceiling, and sidewall on micro-quadrotors. Darius J. Carter, Lauren Bouchard, and Daniel B. Quinn. AIAA Journal, dec 2020. URL, DOI.
[93] Research on relative positioning system of UAVs Swarm based on distributed UWB. Zhenyi Li, Dong Yin, Xiaojia Xiang, Dengqing Tang, Changxin Zhang, and Shuluan Zhang. Proceedings - 2020 Chinese Automation Congress, CAC 2020, nov 2020. DOI.
[94] An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay. Barbara Barros Carlos, Tommaso Sartor, Andrea Zanelli, Gianluca Frison, Wolfram Burgard, Moritz Diehl, and Giuseppe Oriolo. 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020, oct 2020. ArXiv, DOI.
[95] Rotor-induced Airflow for Odor Source Detection on Nano-Quadcopters. Alexander Castro, Leo Peckerar, Timothy Horiuchi, and Pamela Abshire. Proceedings of IEEE Sensors, oct 2020. DOI.
[96] Online Trajectory Generation with Distributed Model Predictive Control for Multi-Robot Motion Planning. Carlos E. Luis, Marijan Vukosavljev, and Angela P. Schoellig. IEEE Robotics and Automation Letters, sep 2020. ArXiv, DOI.
[97] Guarding a Territory against an Intelligent Intruder: Strategy Design and Experimental Verification. Han Fu and Hugh H.T. Liu. IEEE/ASME Transactions on Mechatronics, aug 2020. DOI.
[98] Quadrotor-based lighthouse localization with time-synchronized wireless sensor nodes and bearing-only measurements. Brian G. Kilberg, Felipe M.R. Campos, Craig B. Schindler, and Kristofer S.J. Pister. Sensors (Switzerland), jul 2020. URL, URL, DOI.
[99] ModQuad-DoF: A Novel Yaw Actuation for Modular Quadrotors. Bruno Gabrich, Guanrui Li, and Mark Yim. Proceedings - IEEE International Conference on Robotics and Automation, may 2020. DOI.
[100] Intuitive 3D Control of a Quadrotor in User Proximity with Pointing Gestures. Boris Gromov, Jerome Guzzi, Luca M. Gambardella, and Alessandro Giusti. Proceedings - IEEE International Conference on Robotics and Automation, may 2020. Video, DOI.
[101] Aerodynamic imaging by mosquitoes inspires a surface detector for autonomous flying vehicles. Toshiyuki Nakata, Nathan Phillips, Patrício Simões, Ian J. Russell, Jorn A. Cheney, Simon M. Walker, and Richard J. Bomphrey. Science, may 2020. DOI.
[102] Distributed Consensus Control of Multiple UAVs in a Constrained Environment. Gang Wang, Weixin Yang, Na Zhao, Yunfeng Ji, Yantao Shen, Hao Xu, and Peng Li. Proceedings - IEEE International Conference on Robotics and Automation, may 2020. DOI.
[103] Hand-worn Haptic Interface for Drone Teleoperation. Matteo MacChini, Thomas Havy, Antoine Weber, Fabrizio Schiano, and Dario Floreano. Proceedings - IEEE International Conference on Robotics and Automation, apr 2020. ArXiv, Video, DOI.
[104] Drone proximity detection via air disturbance analysis. Qian Zhao, Jason Hughes, and Damian M. Lyons. https://doi.org/10.1117/12.2556385, apr 2020. URL, URL, DOI.
[105] Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions. Guanya Shi, Wolfgang Honig, Yisong Yue, and Soon Jo Chung. Proceedings - IEEE International Conference on Robotics and Automation, mar 2020. ArXiv, DOI.
[106] Trajectory-based agile multi uav coordination through time synchronisation. Omar Shadeed, Halise Turkmen, and Emre Koyuncu. AIAA Scitech 2020 Forum, 2020. URL, DOI.
[107] Jie Xu. Experimental Implementation of A Distributed Time-Varying Constrained Optimization Algorithm by Using UAVs. PhD thesis, UNIVERSITY OF CALIFORNIA RIVERSIDE, 2020.
[108] Fast and in sync: Periodic swarm patterns for quadrotors. Xintong Du, Carlos E. Luis, Marijan Vukosavljev, and Angela P. Schoellig. Proceedings - IEEE International Conference on Robotics and Automation, oct 2019. ArXiv, Video, DOI.
[109] Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment. K. N. McGuire, C. de Wagter, K. Tuyls, H. J. Kappen, and G. C.H.E. de Croon. Science Robotics, oct 2019. URL, Video, DOI.
[110] Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, and Vijay Janapa Reddi. Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller. sep 2019. ArXiv, Blog, Video.
[111] Unsupervised Tuning of Filter Parameters Without Ground-Truth Applied to Aerial Robots. Shushuai Li, Christophe De Wagter, and Guido C. H. E. de Croon. IEEE Robotics and Automation Letters, jul 2019. DOI.
[112] Indoor Air Quality Monitoring using flying Nanobots: Design and Experimental Study. Patrick P. Neumann, Paul Hirschberger, Zhandos Baurzhan, Carlo Tiebe, Michael Hofmann, Dino Hullmann, and Matthias Bartholmai. ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings, may 2019. DOI.
[113] A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones. Daniele Palossi, Antonio Loquercio, Francesco Conti, Eric Flamand, Davide Scaramuzza, and Luca Benini. IEEE Internet of Things Journal, may 2019. ArXiv, DOI.
[114] Compliant bistable gripper for aerial perching and grasping. Haijie Zhang, Jiefeng Sun, and Jianguo Zhao. Proceedings - IEEE International Conference on Robotics and Automation, may 2019. Video, DOI.
[115] Distributed Localization and Control of Quadrotor UAVs Using Ultra-Wideband Sensors. Bryce Mack, Christopher Noe, Trevor Rice, In Soo Ahn, and Jing Wang. IEEE Aerospace Conference Proceedings, mar 2019. DOI.
[116] Generalization through simulation: Integrating simulated and real data into deep reinforcement learning for vision-based autonomous flight. Katie Kang, Suneel Belkhale, Gregory Kahn, Pieter Abbeel, and Sergey Levine. Proceedings - IEEE International Conference on Robotics and Automation, feb 2019. ArXiv, Video, DOI.
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