Digital Elevation Map estimation by vision-lidar fusion

Malartre, Florent; Feraud, Thomas; Debain, Christophe; Chapuis, Roland

doi:10.1109/robio.2009.5420701

Cited by 10 publications

(7 citation statements)

References 11 publications

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“…The majority of the mapping methods project depth information into digital elevation maps by connecting data points by piecewise continuous cells [22], which are only 1 st order continuous. A search over such a terrain representation results in non-smooth paths that do not allow motion at continuous speeds.…”

Section: Terrain and Path Representationmentioning

confidence: 99%

Pose Estimation of Vehicles Over Uneven Terrain

Ma¹,

Shiller²

2019

Preprint

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This paper presents a method for pose estimation of off-road vehicles moving over uneven terrain. It determines the contact points between the wheels and the terrain, assuming rigid contacts between an arbitrary number of wheels and ground. The terrain is represented by a 3D points cloud, interpolated by a B-patch to provide a continuous terrain representation. The pose estimation problem is formulated as a rigid body contact problem for a given location of the vehicle's center of mass over the terrain and a given yaw angle. The contact points between the wheels and ground are determined by releasing the vehicle from a given point above the terrain, until the contact forces between the wheels and ground, and the gravitational force, reach equilibrium. The contact forces are calculated using singular value decomposition (SVD) of the deduced contact matrix. The proposed method is computationally efficient, allowing real time computation during motion, as demonstrated in several examples. Accurate pose estimations can be used for motion planning, stability analyses and traversability analyses over uneven terrain.

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Section: Terrain and Path Representationmentioning

confidence: 99%

Pose Estimation of Vehicles Over Uneven Terrain

Ma¹,

Shiller²

2019

Preprint

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“…Although the 2-D grid map is effective in avoiding simple obstacles on flat terrain, a detailed grid map is required to handle complex situations. A 2.5-D grid map, a so-called elevation map, contains height information at each cell [14]- [17]. This map is useful for terrain with a single surface layer, but cannot deal with multiple surface layers such as bridges, tunnels, or underpasses.…”

Section: Related Researchmentioning

confidence: 99%

Dense Stereo-Based Robust Vertical Road Profile Estimation Using Hough Transform and Dynamic Programming

Suhr

Jung

2015

IEEE Trans. Intell. Transport. Syst.

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This paper proposes a dense stereo-based robust vertical road profile estimation method. The vertical road profile is modeled by a cubic B-spline curve, which is known to be accurate and flexible but difficult to estimate under a large proportion of outliers. To robustly estimate a cubic B-spline curve, the proposed method utilizes a two-step strategy that initially estimates a piecewise linear function and then obtains a cubic B-spline curve based on the initial estimation result. A Hough transform and dynamic programming are utilized for estimating a piecewise linear function to achieve robustness against outliers and guarantee optimal parameters. In the experiment, a performance evaluation and comparison were conducted using three publicly available databases. The result shows that the proposed method outperforms three previous methods in all databases. In particular, its performance is superior to the others in the cases of a large proportion of outliers and road surfaces distant from the ego-vehicle.Index Terms-B-spline curve, dense stereo, dynamic programming, Hough transform, piecewise linear function, road profile, road surface, stereo vision.

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“…These equations and their respective jacobian matrices are given in [13]. The next step will be to update the state vector X for each time t.…”

Section: B Problem Formulationmentioning

confidence: 99%

Real-time dense digital elevation map estimation using laserscanner and camera SLAM process

Malartre¹,

Delmas²,

Chapuis³

et al. 2010

2010 11th International Conference on Control Automation Robotics &Amp; Vision

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This paper is about environment perception for navigation system in outdoor applications. Unlike other approaches that try to detect an obstacle of binary state, we consider here a Digital Elevation Map (DEM). This map has to be built in regards to the guidance system's needs. These needs depend on the vehicle capabilities, its dynamics constraints, its speed etc... Starting with the navigation system's needs, our goal is to estimate a precise and dense DEM. Our approach is based on a SLAM algorithm combining a 2D rangefinder and a camera. Thus we can estimate both the displacement between two laser scan and have a good density of the reconstructed DEM. The approach has been validated both using simulated realistic data and real data in real-time on our robot in outdoor environment (approx. 40ms per loop).

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Digital Elevation Map estimation by vision-lidar fusion

Cited by 10 publications

References 11 publications

Pose Estimation of Vehicles Over Uneven Terrain

Pose Estimation of Vehicles Over Uneven Terrain

Dense Stereo-Based Robust Vertical Road Profile Estimation Using Hough Transform and Dynamic Programming

Real-time dense digital elevation map estimation using laserscanner and camera SLAM process

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