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

By Giuseppe Loianno, Chris Brunner, Gary G. Mcgrath, Vijay R. Kumar. 2017

292 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

In Biomedical Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing (2018, methodology): “Traditional approaches to autonomous MAV navigation build on visual inertial odometry (VIO) [5], [1], [13], [24] or simultaneous localization and mapping (SLAM) [21], [23], which are used to provide a pose estimate of the drone relative to an internal metric map [14], [4].”
Deep Drone Racing: Learning Agile Flight in Dynamic Environments (2018, methodology): “To fully understand the potential and limitations of our approach we compared to a diverse set of baselines, such as a classic approach based on planning and tracking [16] and human pilots of different skill levels.”
PAMPC: Perception-Aware Model Predictive Control for Quadrotors (2018, background): “This made it possible to replicate some of the impressive quadrotor maneuvers seen in the last decade [1], [2], [3], [4], which relied on motion-capture systems, using only onboard sensing, such as cameras and IMUs [5], [6], [7].”
Aggressive quadrotor flight through narrow gaps with onboard sensing and computing using active vision (2016, methodology): “In [8], the authors proposed methods for onboard visionbased state estimation, planning, and control for small quadrotors, and validated the approach in a number of agile maneuvers, among which flying through an inclined gap.”
Visual-Inertial Navigation Algorithm Development Using Photorealistic Camera Simulation in the Loop (2018, background): “To the best of our knowledge the only two demonstrations of on-board, vision-based navigation through window openings come from Loianno et al. [38] and Falanga et al. [39].”
Swarm of micro flying robots in the wild (2022, background): “Formation flight is widely used in drone light shows and has been demonstrated in cooperative transportation (43, 32), but all these demonstrations are presented in empty or manually controlled environments.”
Geometrically Constrained Trajectory Optimization for Multicopters (2021, methodology): “It should be highlighted that our method differs from traditional planners for narrow gaps (Falanga et al. 2017; Loianno et al. 2016) in its flexibility, efficiency and high fidelity.”
Comparison of Trajectory Optimization Algorithms for High-Speed Quadrotor Flight Near Obstacles (2018, methodology): “There have been numerous impressive demonstrations using this type of algorithm, including flight through narrow vertical windows [4], [6] and through restrictive indoor environments [1], [7], [8].”