Stereo vision and terrain modeling for quadruped robots

Kolter, J. Zico; Kim, Young‐Jun; Ng, Andrew Y.

doi:10.1109/robot.2009.5152795

Cited by 64 publications

(45 citation statements)

References 23 publications

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“…Stereo vision has been used for terrain modeling with walking robots so far only in few projects, mostly because typical stereo systems impose high costs of 3D points computation. In the works of Kolter et al (2009) and Rusu et al (2009) walking robots with stereo-based perception are shown to autonomously traverse a rugged terrain, but in both cases the computations are performed off-board, and explicit propagation of the spatial uncertainty from the stereo data to the elevation map is not taken into account. The knowledge about the elevation uncertainty of each cell in the map allows planning the path of the walking robot more efficiently, while avoiding uncertain areas (Belter and Skrzypczyński, 2011b).…”

Section: Related Workmentioning

confidence: 99%

RGB–D terrain perception and dense mapping for legged robots

Belter

Łabęcki

Fankhauser

et al. 2016

International Journal of Applied Mathematics and Computer Science

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This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.

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Section: Related Workmentioning

confidence: 99%

RGB–D terrain perception and dense mapping for legged robots

Belter

Łabęcki

Fankhauser

et al. 2016

International Journal of Applied Mathematics and Computer Science

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“…Kolter et al in [13] took a step further in autonomy by removing the dependence on given maps and external state input. In their control framework they use a well established point-cloud matching technique to iteratively build a map of their environment and afterwards navigate in it.…”

Section: Related Workmentioning

confidence: 99%

Onboard perception-based trotting and crawling with the Hydraulic Quadruped Robot (HyQ)

Havoutis

Ortiz

Bazeille

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper presents a framework developed to increase the autonomy and versatility of a large (∼75kg) hydraulically actuated quadrupedal robot. It combines onboard perception with two locomotion strategies, a dynamic trot and a static crawl gait. This way the robot can perceive its environment and arbitrate between the two behaviours according to the situation at hand. All computations are performed on-board and are carried out in two separate computers, one handles the high-level processes while the other is concerned with the low-level hard real-time control. The perception and subsequently the appropriate gait modifications are performed autonomously. We present outdoor experimental trials of the robot trotting over unknown terrain, perceiving a large obstacle, altering its behaviour to the cautious crawl gait and stepping onto the obstacle. This allows the robot to locomote quickly on relatively flat terrain and gives the robot the ability to overcome large irregular obstacles when required.

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“…Miller (2002) fused the measurements from a laser range finder and a calibrated camera mounted on a helicopter to construct terrain models. Another camera-based approach was proposed recently by Kolter, Kim, and Ng (2009), who equipped a quadruped robot with a stereo-camera system and dealt with the problem of how to infer a dense elevation map of the terrain from the sparse stereo correspondences. Popular approaches from the computer vision literature that do not require a stereo setup are to extract 3D shape from shading (Bors, Hancock, & Wilson, 2003) or from shadows (Daum & Dudek, 1998).…”

Section: Related Workmentioning

confidence: 99%

A Bayesian regression approach to terrain mapping and an application to legged robot locomotion

Plagemann

Mischke

Prentice

et al. 2009

Journal of Field Robotics

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We deal with the problem of learning probabilistic models of terrain surfaces from sparse and noisy elevation measurements. The key idea is to formalize this as a regression problem and to derive a solution based on nonstationary Gaussian processes. We describe how to achieve a sparse approximation of the model, which makes the model applicable to real-world data sets. The main benefits of our model are that (1) it does not require a discretization of space, (2) it also provides the uncertainty for its predictions, and (3) it adapts its covariance function to the observed data, allowing more accurate inference of terrain elevation at points that have not been observed directly. As a second contribution, we describe how a legged robot equipped with a laser range finder can utilize the developed terrain model to plan and execute a path over rough terrain. We show how a motion planner can use the learned terrain model to plan a path to a goal location, using a terrain-specific cost model to accept or reject candidate footholds. To the best of our knowledge, this was the first legged robotics system to autonomously sense, plan, and traverse a terrain surface of the given complexity. C 2009 Wiley Periodicals, Inc.

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Stereo vision and terrain modeling for quadruped robots

Cited by 64 publications

References 23 publications

RGB–D terrain perception and dense mapping for legged robots

RGB–D terrain perception and dense mapping for legged robots

Onboard perception-based trotting and crawling with the Hydraulic Quadruped Robot (HyQ)

A Bayesian regression approach to terrain mapping and an application to legged robot locomotion

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