Stereo vision‐based autonomous navigation for lunar rovers

Cui, Pingyuan; Yue, Fuzhan

doi:10.1108/00022660710758268

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…As the Earth's surface is approximated by a plane [3,9], a normal vector to the plane, n w can be described as: If the horizon line is described by a point X p w and a direction vector l w tangential to the line of horizon visible to the image plane, then:…”

Section: Image Processing Modulementioning

confidence: 99%

“…As the Earth's surface is approximated by a plane [3,9], a normal vector to the plane, n w can be described as:…”

Section: Image Processing Modulementioning

confidence: 99%

“…The SIFT features detected in the current frame were matched to the pre-built database map in order to obtain the location of the vehicle. Stereo vision-based navigation systems were proposed by various authors including Cui et al [3] and Matsumoto et al [4] proposed a representation of the visual route taken by robots in appearance-based navigation. This approach was called the View-Sequenced Route Representation (VSRR) and was a sequence of images memorized in the recording run along the required route.…”

Section: Introductionmentioning

confidence: 99%

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A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications

Sabatini¹,

Richardson²,

Bartel³

et al. 2013

J Aeronaut Aerospace Eng

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A low cost navigation system based on Vision Based Navigation (VBN) and other avionics sensors is presented, which is designed for small size Unmanned Aerial Vehicle (UAV) applications. The main objective of our research is to design a compact, lightweight and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of a small UAV, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UAV platform in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is performed in a significant portion of the AEROSONDE UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture (VBN/IMU/GPS) shows that the integrated system can reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of the second system architecture (VBN/IMU/GPS/ADM) also shows promising results since the achieved attitude accuracy is higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed.A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications Citation: Roberto Sabatini R, Richardson M, Bartel C, Shaid T, Ramasamy S (2013) A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications. J Aeronaut Aerospace Eng 2: 110. doi:10.4172/2168-9792.1000110 Page 2 of 16Volume 2 • Issue 2 • 1000110 J Aeronaut Aerospace Eng ISSN: 2168-9792 JAAE, an open...

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Section: Image Processing Modulementioning

confidence: 99%

“…As the Earth's surface is approximated by a plane [3,9], a normal vector to the plane, n w can be described as:…”

Section: Image Processing Modulementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications

Sabatini¹,

Richardson²,

Bartel³

et al. 2013

J Aeronaut Aerospace Eng

View full text Add to dashboard Cite

show abstract

“…They were equipped with three types of stereo cameras which allowed them to navigate the Martian surface for long distances. A stereo vision-based navigation system for lunar rovers was proposed by Cui [3]. The system performed robust motion estimation and disparity estimation using stereo images.…”

Section: Introductionmentioning

confidence: 99%

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Sabatini

Bartel

Kaharkar

et al. 2012

Optical Sensing and Detection II

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In this paper we present a novel Navigation and Guidance System (NGS) for Unmanned Aerial Vehicles (UAVs) based on Vision Based Navigation (VBN) and other avionics sensors. The main objective of our research is to design a lowcost and low-weight/volume NGS capable of providing the required level of performance in all flight phases of modern small-to medium-size UAVs, with a special focus on automated precision approach and landing, where VBN techniques can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the platform in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is performed in a significant portion of the Aerosonde UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture (VBN/GPS/IMU) shows that the integrated system can reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of the second system architecture (VBN/GPS/IMU/ADM) shows promising results since the achieved attitude accuracy is higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for a frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed. Finally, the output provided by the VBN and integrated navigation sensor systems is used to design a flight control system using a hybrid Fuzzy Logic and Proportional-Integral-Derivative (PID) controller for the Aerosonde UAV.

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Straight-line constrained optical flow monocular visual odometry

Liu

Chen

et al. 2017

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

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Stereo vision‐based autonomous navigation for lunar rovers

Cited by 4 publications

References 14 publications

A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications

A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Straight-line constrained optical flow monocular visual odometry

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