A self-rotating, single-actuated UAV with extended sensor field of view for autonomous navigation

Uncrewed aerial vehicles (UAVs) rely heavily on visual sensors to perceive obstacles and explore environments. Current UAVs are limited in both perception capability and task efficiency because of a small sensor field of view (FoV). One solution could be to leverage self-rotation in UAVs to extend the sensor FoV without consuming extra power. This natural mechanism, induced by the counter-torque of the UAV motor, has rarely been exploited by existing autonomous UAVs because of the difficulties in design and control due to highly coupled and nonlinear dynamics and the challenges in navigation brought by the high-rate self-rotation. Here, we present powered-flying ultra-underactuated LiDAR (light detection and ranging) sensing aerial robot (PULSAR), an agile and self-rotating UAV whose three-dimensional position is fully controlled by actuating only one motor to obtain the required thrust and moment. The use of a single actuator effectively reduces the energy loss in powered flights. Consequently, PULSAR consumes 26.7% less power than the benchmarked quadrotor with the same total propeller disk area and avionic payloads while retaining a good level of agility. Augmented by an onboard LiDAR sensor, PULSAR can perform autonomous navigation in unknown environments and detect both static and dynamic obstacles in panoramic views without any external instruments. We report the experiments of PULSAR in environment exploration and multidirectional dynamic obstacle avoidance with the extended FoV via self-rotation, which could lead to increased perception capability, task efficiency, and flight safety. Description PULSAR achieves autonomous three-dimensional UAV navigation with a single actuator.

[1]  Lei Ma,et al.  A Flexibly Assembled and Maneuverable Reconfigurable Modular Multirotor Aerial Vehicle , 2022, IEEE/ASME Transactions on Mechatronics.

[2]  P. Chirarattananon,et al.  A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight , 2022, Science Robotics.

[3]  Hong Xie,et al.  FAEP: Fast Autonomous Exploration Planner for UAV Equipped with Limited FOV Sensor , 2022, ArXiv.

[4]  E. Koyuncu,et al.  Deep Reinforcement Learning based Aggressive Collision Avoidance with Limited FOV for Unmanned Aerial Vehicles , 2022, AIAA SCITECH 2022 Forum.

[5]  Bin Xian,et al.  Fault-Tolerant Position Tracking Control Design for a Tilt Tri-Rotor Unmanned Aerial Vehicle , 2022, IEEE Transactions on Industrial Electronics.

[6]  Shane Kyi Hla Win,et al.  Design and control of the first foldable single-actuator rotary wing micro aerial vehicle , 2021, Bioinspiration & biomimetics.

[7]  Davide Scaramuzza,et al.  Time-optimal planning for quadrotor waypoint flight , 2021, Science Robotics.

[8]  Yixi Cai,et al.  FAST-LIO2: Fast Direct LiDAR-Inertial Odometry , 2021, IEEE Transactions on Robotics.

[9]  Gim Song Soh,et al.  An Agile Samara-Inspired Single-Actuator Aerial Robot Capable of Autorotation and Diving , 2021, IEEE Transactions on Robotics.

[10]  Sebastian Scherer,et al.  Super Odometry: IMU-centric LiDAR-Visual-Inertial Estimator for Challenging Environments , 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[11]  Eckehard Steinbach,et al.  LoLa-SLAM: Low-Latency LiDAR SLAM Using Continuous Scan Slicing , 2021, IEEE Robotics and Automation Letters.

[12]  Chengxi Yu,et al.  Leader-Follower Formation for UAVs with FOVs Constraint , 2021, 2021 22nd IEEE International Conference on Industrial Technology (ICIT).

[13]  Fei Gao,et al.  FAST-Dynamic-Vision: Detection and Tracking Dynamic Objects with Event and Depth Sensing , 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[14]  Wei Xu,et al.  Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots , 2021, ArXiv.

[15]  Davide Scaramuzza,et al.  Autonomous Quadrotor Flight Despite Rotor Failure With Onboard Vision Sensors: Frames vs. Events , 2021, IEEE Robotics and Automation Letters.

[16]  Wei Xu,et al.  ikd-Tree: An Incremental K-D Tree for Robotic Applications , 2021, ArXiv.

[17]  Victor Massagué Respall,et al.  Unmanned Aerial Vehicle Path Planning for Exploration Mapping , 2020, 2020 International Conference Nonlinearity, Information and Robotics (NIR).

[18]  Minas Liarokapis,et al.  An Agile, Coaxial, Omnidirectional Rotor Module: On the Development of Hybrid, All Terrain Robotic Rotorcrafts , 2020, 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

[19]  A. Kolaei,et al.  Aerodynamic Interactions of Quadrotor Configurations , 2020 .

[20]  Gim Song Soh,et al.  Achieving Efficient Controlled Flight with A Single Actuator , 2020, 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[21]  Roman Fedorenko,et al.  Regions of Interest Segmentation from LiDAR Point Cloud for Multirotor Aerial Vehicles , 2020, 2020 International Conference on Unmanned Aircraft Systems (ICUAS).

[22]  Davide Scaramuzza,et al.  Dynamic obstacle avoidance for quadrotors with event cameras , 2020, Science Robotics.

[23]  Fei Gao,et al.  Autonomous aerial robot using dual‐fisheye cameras , 2020, J. Field Robotics.

[24]  Adrian Lee,et al.  Gemini: A Compact Yet Efficient Bi-Copter UAV for Indoor Applications , 2020, IEEE Robotics and Automation Letters.

[25]  Pakpong Chirarattananon,et al.  Design and Take-Off Flight of a Samara-Inspired Revolving-Wing Robot , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[26]  Tom Drummond,et al.  Event-Based Motion Segmentation by Motion Compensation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[27]  Narayanan Komerath,et al.  Multirotor Drone Aerodynamic Interaction Investigation , 2018, Drones.

[28]  Jun Zhu,et al.  Downside Hemisphere Object Detection and Localization of MAV by Fisheye Camera , 2018, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV).

[29]  Mohammad Bagher Menhaj,et al.  Design and Construction of Monocopter and its Nonlinear Control Using Photo Diode Array , 2018, U.Porto Journal of Engineering.

[30]  Teodor Tomic,et al.  Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[31]  Damian Wierzbicki,et al.  Multi-Camera Imaging System for UAV Photogrammetry , 2018, Sensors.

[32]  Mark Yim,et al.  Emulating a Fully Actuated Aerial Vehicle Using Two Actuators , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[33]  Roland Siegwart,et al.  Receding horizon path planning for 3D exploration and surface inspection , 2018, Auton. Robots.

[34]  Mark Yim,et al.  Scalability of Cyclic Control without Blade Pitch Actuators , 2018 .

[35]  Anthony A. Maciejewski,et al.  Robust UAV path planning using POMDP with limited FOV sensor , 2017, 2017 IEEE Conference on Control Technology and Applications (CCTA).

[36]  Hui Hu,et al.  An Experimental Investigation on Rotor-to-Rotor Interactions of Small UAV Propellers , 2017 .

[37]  Mark Yim,et al.  Piccolissimo: The smallest micro aerial vehicle , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[38]  Jieru Zhao,et al.  Modeling and attitude control of Bi-copter , 2016, 2016 IEEE International Conference on Aircraft Utility Systems (AUS).

[39]  Emil Fresk,et al.  Design, modelling and control of a Single Rotor UAV , 2016, 2016 24th Mediterranean Conference on Control and Automation (MED).

[40]  Raffaello D'Andrea,et al.  A controllable flying vehicle with a single moving part , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[41]  Kingsley Fregene,et al.  Micro air vehicle based navigation aiding in degraded environments , 2016, 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS).

[42]  Roland Siegwart,et al.  Omnidirectional visual obstacle detection using embedded FPGA , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[43]  Lu Fang,et al.  Guidance: A visual sensing platform for robotic applications , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[44]  Mark Yim,et al.  Flight performance of a swashplateless micro air vehicle , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[45]  Adam Harmat,et al.  Multi-Camera Tracking and Mapping for Unmanned Aerial Vehicles in Unstructured Environments , 2014, Journal of Intelligent & Robotic Systems.

[46]  Mark Yim,et al.  Passive stability of a single actuator micro aerial vehicle , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[47]  Upamanyu Madhow,et al.  GPS-optimal micro air vehicle navigation in degraded environments , 2014, 2014 American Control Conference.

[48]  Mark Yim,et al.  An underactuated propeller for attitude control in micro air vehicles , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[49]  Maxim Likhachev,et al.  Path planning for non-circular micro aerial vehicles in constrained environments , 2013, 2013 IEEE International Conference on Robotics and Automation.

[50]  Ming Chang,et al.  Lockheed Martin's SAMARAI Nano Air Vehicle: Challenges, Research, and Realization , 2012 .

[51]  Erdinç Altug,et al.  EKF Based Attitude Estimation and Stabilization of a Quadrotor UAV Using Vanishing Points in Catadioptric Images , 2011, J. Intell. Robotic Syst..

[52]  Evan R. Ulrich,et al.  From falling to flying: the path to powered flight of a robotic samara nano air vehicle , 2010, Bioinspiration & biomimetics.

[53]  David,et al.  Development and Flight Validation of an Autonomous Mono-Wing UAS , 2010 .

[54]  Simon Lacroix,et al.  UAV target tracking using an adversarial iterative prediction , 2009, 2009 IEEE International Conference on Robotics and Automation.

[55]  Steven Lake Waslander,et al.  Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering , 2009, 2009 IEEE International Conference on Robotics and Automation.

[56]  Alex Gurtner,et al.  Investigation of Fish-Eye Lenses for Small-UAV Aerial Photography , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[57]  Stefan Gottschalk,et al.  Aerodynamics Aeronautics And Flight Mechanics , 2016 .

[58]  D. Verstraete,et al.  The Effects of Blockage on the Performance of Small Propellers , 2016 .

[59]  Michael S. Selig,et al.  Reynolds number effects on the performance of small-scale propellers , 2014 .