Landmark-based navigation in large-scale outdoor environments

Faßbender, Dennis; Kusenbach, Michael; Wuensche, Hans-Joachim

doi:10.1109/iros.2015.7354008

Cited by 13 publications

(4 citation statements)

References 14 publications

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“…Traditionally landmark-based navigation has been approached in two ways, i) as a simultaneously mapping and localisation problem, ii) as the process of constructing some type of topological or metric-based maps [11]. However, there exist methods that do not explicitly reconstruct the scene or create a map.…”

Section: Related Workmentioning

confidence: 99%

“…The idea behind our approach is to introduce a term in (11) that is function of the feature location so that the rotational components are minimised until the features are close enough to their desired location. Our function has the form…”

Section: Proposed Approachmentioning

confidence: 99%

“…Exponential or decay functions have this property in which the growth or decay rate can be set, in our case, proportional to the error e = s − s * such that f (s) = k 1 e k2(1−e) where k 1 and k 2 are gains that regulate rate of decay and upper/lower function limits. The following step is to introduce this function in (11) such thatv…”

Section: Proposed Approachmentioning

confidence: 99%

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Visual Controllers for Relative Positioning in Indoor Settings

Mejias

Campoy

2019

2019 International Conference on Unmanned Aircraft Systems (ICUAS)

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This paper presents an approach to visually control a quadrotor relative to known landmarks. Relative positioning is achieved here by a new decoupled approach to image based visual servoing (IBVS), in which rotational and translational coupling is minimised by introducing a decay function that is proportional to feature location in the image. Simulations and experiments were conducted to validate the proposed method. Results show that our method has benefits over standard decoupled IBVS by ensuring smoother trajectories in the image plane as well as in task space, minimising the risk of features leaving the image plane.

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Section: Related Workmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

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Visual Controllers for Relative Positioning in Indoor Settings

Mejias

Campoy

2019

2019 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…On the contrary local features are robust to different image variations. The local features include points [8], [9], line segments [10], [11], contours [12] and even objects [13].…”

Section: Introductionmentioning

confidence: 99%

Linear Features Observation Model for Autonomous Vehicle Localization

Shipitko¹,

Kibalov²,

Abramov³

2020

Preprint

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Precise localization is a core ability of an autonomous vehicle. It is a prerequisite for motion planning and execution. The well-established localization approaches such as Kalman and particle filters require a probabilistic observation model allowing to compute a likelihood of measurement given a system state vector, usually vehicle pose, and a map. The higher precision of the localization system may be achieved through the development of a more sophisticated observation model considering various measurement error sources. Meanwhile model needs to be simple to be computable in real-time. This paper proposes an observation model for visually detected linear features. Examples of such features include, but not limited to, road markings and road boundaries. The proposed observation model depicts two core detection error sources: shift error and angular error. It also considers the probability of false-positive detection. The structure of the proposed model allows precomputing and incorporating the measurement error directly into the map represented by a multichannel digital image. Measurement error precomputation and storing the map as an image speeds up observation likelihood computation and in turn localization system. The experimental evaluation on real autonomous vehicle demonstrates that the proposed model allows for precise and reliable localization in a variety of scenarios.

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A Tri-Dipole based Location and Orientation Estimation Method in Near Magnetic Field

Sun

Hsieh

et al. 2018

2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

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Landmark-based navigation in large-scale outdoor environments

Cited by 13 publications

References 14 publications

Visual Controllers for Relative Positioning in Indoor Settings

Visual Controllers for Relative Positioning in Indoor Settings

Linear Features Observation Model for Autonomous Vehicle Localization

A Tri-Dipole based Location and Orientation Estimation Method in Near Magnetic Field

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