TY - GEN
T1 - Aggressive Visual Perching with Quadrotors on Inclined Surfaces
AU - Mao, Jeffrey
AU - Li, Guanrui
AU - Nogar, Stephen
AU - Kroninger, Christopher
AU - Loianno, Giuseppe
N1 - Funding Information:
This work was supported by the ARL grant DCIST CRA W911NF-17-2-0181 and the young researchers program ”Rita Levi di Montalcini” 2017 grant PGR17W9W4N.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for surveillance and monitoring tasks. By perching and staring on one or multiple locations aerial robots can save energy while concurrently increasing their overall mission time without actively flying. In this paper, we address the estimation, planning, and control problems for autonomous perching on inclined surfaces with small quadrotors using visual and inertial sensing. We focus on planning and executing dynamically feasible trajectories to navigate and perch to a desired target location with on board sensing and computation. Our planner also supports certain classes of nonlinear global constraints by leveraging an efficient algorithm that we have mathematically verified. The on board cameras and IMU are concurrently used for state estimation and to infer the relative robot/target localization. The proposed solution runs in real-time on board a limited computational unit. Experimental results validate the proposed approach by tackling aggressive perching maneuvers with flight envelopes that include large excursions from the hover position on inclined surfaces up to 90°, angular rates up to 600 deg/s, and accelerations up to 10 m/s2.
AB - Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for surveillance and monitoring tasks. By perching and staring on one or multiple locations aerial robots can save energy while concurrently increasing their overall mission time without actively flying. In this paper, we address the estimation, planning, and control problems for autonomous perching on inclined surfaces with small quadrotors using visual and inertial sensing. We focus on planning and executing dynamically feasible trajectories to navigate and perch to a desired target location with on board sensing and computation. Our planner also supports certain classes of nonlinear global constraints by leveraging an efficient algorithm that we have mathematically verified. The on board cameras and IMU are concurrently used for state estimation and to infer the relative robot/target localization. The proposed solution runs in real-time on board a limited computational unit. Experimental results validate the proposed approach by tackling aggressive perching maneuvers with flight envelopes that include large excursions from the hover position on inclined surfaces up to 90°, angular rates up to 600 deg/s, and accelerations up to 10 m/s2.
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U2 - 10.1109/IROS51168.2021.9636690
DO - 10.1109/IROS51168.2021.9636690
M3 - Conference contribution
AN - SCOPUS:85124344488
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 5242
EP - 5248
BT - IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Y2 - 27 September 2021 through 1 October 2021
ER -