Estimation, Control, and Planning for Aggressive Flight With a Small Quadrotor With a Single Camera and IMU

We address the state estimation, control, and planning for aggressive flight with a 150 cm diameter, 250 g quadrotor equipped only with a single camera and an inertial measurement unit (IMU). The use of smartphone grade hardware and the small scale provides an inexpensive and practical solution for autonomous flight in indoor environments. The key contributions of this paper are: 1) robust state estimation and control using only a monocular camera and an IMU at speeds of 4.5 m/s, accelerations of over 1.5 g, roll and pitch angles of up to 90°, and angular rate of up to 800°/s without requiring any structure in the environment; 2) planning of dynamically feasible three-dimensional trajectories for slalom paths and flights through narrow windows; and 3) extensive experimental results showing aggressive flights through and around obstacles with large rotation angular excursions and accelerations.

[1]  Davide Scaramuzza,et al.  Event-based, 6-DOF pose tracking for high-speed maneuvers , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Vijay Kumar,et al.  Cooperative localization and mapping of MAVs using RGB-D sensors , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[3]  Pieter Abbeel,et al.  Apprenticeship learning and reinforcement learning with application to robotic control , 2008 .

[4]  Taeyoung Lee,et al.  Nonlinear robust tracking control of a quadrotor UAV on SE(3) , 2011, 2012 American Control Conference (ACC).

[5]  Vijay Kumar,et al.  The GRASP Multiple Micro-UAV Testbed , 2010, IEEE Robotics & Automation Magazine.

[6]  Flavio Fontana,et al.  Automatic re-initialization and failure recovery for aggressive flight with a monocular vision-based quadrotor , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[7]  Vijay Kumar,et al.  Trajectory generation and control for precise aggressive maneuvers with quadrotors , 2012, Int. J. Robotics Res..

[8]  Darius Burschka,et al.  Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue , 2012, IEEE Robotics & Automation Magazine.

[9]  Claire J. Tomlin,et al.  Design of guaranteed safe maneuvers using reachable sets: Autonomous quadrotor aerobatics in theory and practice , 2010, 2010 IEEE International Conference on Robotics and Automation.

[10]  Javier Civera,et al.  Inverse Depth Parametrization for Monocular SLAM , 2008, IEEE Transactions on Robotics.

[11]  Vijay Kumar,et al.  Smartphones power flying robots , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[12]  Vincenzo Lippiello,et al.  Aerial service vehicles for industrial inspection: task decomposition and plan execution , 2013, Applied Intelligence.

[13]  Vijay Kumar,et al.  Vision-Based State Estimation and Trajectory Control Towards High-Speed Flight with a Quadrotor , 2013, Robotics: Science and Systems.

[14]  Stefano Soatto,et al.  Visual-inertial navigation, mapping and localization: A scalable real-time causal approach , 2011, Int. J. Robotics Res..

[15]  Roland Siegwart,et al.  Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments , 2011, J. Field Robotics.

[16]  Vijay Kumar,et al.  Inspection of Penstocks and Featureless Tunnel-like Environments Using Micro UAVs , 2013, FSR.

[17]  Dimitrios G. Kottas,et al.  Camera-IMU-based localization: Observability analysis and consistency improvement , 2014, Int. J. Robotics Res..

[18]  Raffaello D'Andrea,et al.  A simple learning strategy for high-speed quadrocopter multi-flips , 2010, 2010 IEEE International Conference on Robotics and Automation.

[19]  Gaurav S. Sukhatme,et al.  Visual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration , 2011, Int. J. Robotics Res..

[20]  Kazuya Yoshida,et al.  Collaborative mapping of an earthquake‐damaged building via ground and aerial robots , 2012, J. Field Robotics.

[21]  Lorenzo Marconi,et al.  Impedance control of an aerial manipulator , 2012, 2012 American Control Conference (ACC).

[22]  Agostino Martinelli,et al.  Visual-inertial structure from motion: Observability and resolvability , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Vijay Kumar,et al.  Tightly-coupled monocular visual-inertial fusion for autonomous flight of rotorcraft MAVs , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[24]  S SukhatmeGaurav,et al.  Visual-Inertial Sensor Fusion , 2011 .

[25]  Vijay Kumar,et al.  Visual Servoing of Quadrotors for Perching by Hanging From Cylindrical Objects , 2016, IEEE Robotics and Automation Letters.

[26]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.