Vision-based fast navigation of micro aerial vehicles

Giuseppe Loianno, Vijay Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address the key challenges for autonomous fast flight for Micro Aerial Vehicles (MAVs) in 3-D, cluttered environments. For complete autonomy, the system must identify the vehicle's state at high rates, using either absolute or relative asynchronous on-board sensor measurements, use these state estimates for feedback control, and plan trajectories to the destination. State estimation requires information from different sensors to be fused, exploiting information from different, possible asynchronous sensors at different rates. In this work, we present techniques in the area of planning, control and visual-inertial state estimation for fast navigation of MAVs. We demonstrate how to solve on-board, on a small computational unit, the pose estimation, control and planning problems for MAVs, using a minimal sensor suite for autonomous navigation composed of a single camera and IMU. Additionally, we show that a consumer electronic device such as a smartphone can alternatively be employed for both sensing and computation. Experimental results validate the proposed techniques. Any consumer, provided with a smartphone, can autonomously drive a quadrotor platform at high speed, without GPS, and concurrently build 3-D maps, using a suitably designed app.

Original languageEnglish (US)
Title of host publicationMicro- and Nanotechnology Sensors, Systems, and Applications VIII
EditorsThomas George, Achyut K. Dutta, M. Saif Islam
PublisherSPIE
Volume9836
ISBN (Electronic)9781510600775
DOIs
StatePublished - Jan 1 2016
EventMicro- and Nanotechnology Sensors, Systems, and Applications VIII Conference - Baltimore, United States
Duration: Apr 17 2016Apr 21 2016

Other

OtherMicro- and Nanotechnology Sensors, Systems, and Applications VIII Conference
CountryUnited States
CityBaltimore
Period4/17/164/21/16

Fingerprint

navigation
Navigation
vehicles
Antennas
state estimation
Sensor
Smartphones
sensors
Sensors
State Estimation
State estimation
3D
planning
Planning
autonomous navigation
autonomy
Autonomous Navigation
Consumer electronics
Pose Estimation
feedback control

Keywords

  • Navigation
  • UAVs
  • Visual localization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Loianno, G., & Kumar, V. (2016). Vision-based fast navigation of micro aerial vehicles. In T. George, A. K. Dutta, & M. S. Islam (Eds.), Micro- and Nanotechnology Sensors, Systems, and Applications VIII (Vol. 9836). [98361T] SPIE. https://doi.org/10.1117/12.2224520

Vision-based fast navigation of micro aerial vehicles. / Loianno, Giuseppe; Kumar, Vijay.

Micro- and Nanotechnology Sensors, Systems, and Applications VIII. ed. / Thomas George; Achyut K. Dutta; M. Saif Islam. Vol. 9836 SPIE, 2016. 98361T.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Loianno, G & Kumar, V 2016, Vision-based fast navigation of micro aerial vehicles. in T George, AK Dutta & MS Islam (eds), Micro- and Nanotechnology Sensors, Systems, and Applications VIII. vol. 9836, 98361T, SPIE, Micro- and Nanotechnology Sensors, Systems, and Applications VIII Conference, Baltimore, United States, 4/17/16. https://doi.org/10.1117/12.2224520
Loianno G, Kumar V. Vision-based fast navigation of micro aerial vehicles. In George T, Dutta AK, Islam MS, editors, Micro- and Nanotechnology Sensors, Systems, and Applications VIII. Vol. 9836. SPIE. 2016. 98361T https://doi.org/10.1117/12.2224520
Loianno, Giuseppe ; Kumar, Vijay. / Vision-based fast navigation of micro aerial vehicles. Micro- and Nanotechnology Sensors, Systems, and Applications VIII. editor / Thomas George ; Achyut K. Dutta ; M. Saif Islam. Vol. 9836 SPIE, 2016.
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