Development of an integrated sensor system for obstacle detection and terrain evaluation for application to unmanned ground vehicles

Crane, Carl D.; Armstrong, David G.; Ahmed, Maryum; Solanki, S. K.; MacArthur, Donald; Zawodny, E.; Gray, Sarah A. O.; Petroff, Thomas; Grifis, Mike; Evans, Carl

doi:10.1117/12.603563

Cited by 7 publications

(3 citation statements)

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“…Therefore the degree of uncertainty is higher than in autonomous driving systems. Crane et al [20] propose a sensor system with four different sensor types to identify obstacles. A sensor fusion approach that was developed whereby the output of all sensors was in a common grid based format.…”

Section: Blind Users Navigation and Orientationmentioning

confidence: 99%

Exploring Smart Environments Through Human Computation for Enhancing Blind Navigation

Paredes

Fernandes

Sousa

et al. 2015

Communications in Computer and Information Science

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Abstract. In this paper the orchestration of wearable sensors with human computation is explored to provide map metadata for blind navigation. Technological navigation aids for blind must provide accurate information about the environment and select the best path to reach a chosen destination. Urban barriers represent dangers for the blind users. The dynamism of smart cities promotes a constant change of these dangers and therefore a potentially "dangerous territory" for these users. Previous work demonstrated that redundant solutions in smart environments complemented by human computation could provide a reliable and trustful data source for a new generation of blind navigation systems. We propose and discuss a modular architecture, which interacts with environmental sensors to gather information and process the acquired data with advanced algorithms empowered by human computation. The gathered metadata should enable the creation of "happy maps" that are delivered to blind users through a previously developed navigation system.

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Section: Blind Users Navigation and Orientationmentioning

confidence: 99%

Exploring Smart Environments Through Human Computation for Enhancing Blind Navigation

Paredes

Fernandes

Sousa

et al. 2015

Communications in Computer and Information Science

View full text Add to dashboard Cite

show abstract

“…Stereo vision is one of the most active research areas in mobile robot navigation based on vision [1]. When the robot in the unknown environment moves in the desired direction, it should be able to distinguish the positions and sizes of the obstacles, and to plan the available path.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming

Bai

Zhuang

Wang

2009

J. Control Theory Appl.

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An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points (GCPs) is presented. To decrease time complexity without losing matching precision, using a multilevel search scheme, the coarse matching is processed in typical disparity space image, while the fine matching is processed in disparity-offset space image. In the upper level, GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint. Under the supervision of the highly reliable GCPs, bidirectional dynamic programming framework is employed to solve the inconsistency in the optimization path. In the lower level, to reduce running time, disparity-offset space is proposed to efficiently achieve the dense disparity image. In addition, an adaptive dual support-weight strategy is presented to aggregate matching cost, which considers photometric and geometric information. Further, post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm, where missing stereo information is substituted from surrounding regions. To demonstrate the effectiveness of the algorithm, we present the two groups of experimental results for four widely used standard stereo data sets, including discussion on performance and comparison with other methods, which show that the algorithm has not only a fast speed, but also significantly improves the efficiency of holistic optimization.

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“…That is one of the most active research areas in aerospace. Stereo vision is applied to this field widely because it is non‐osculant, high‐accurate and low‐cost (Crane et al , 2005). Rover must distinguish between roadblock and road from unknown environment accurately and rapidly.…”

Section: Introductionmentioning

confidence: 99%

Local‐global stereo matching algorithm

Zhao

Cai

2006

Aircraft Engineering and Aerospace Technology

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PurposeIn order to solve the problem that dynamic programming (DP) stereo algorithm is slow, a local‐global stereo matching algorithm is presented. In this method, local and global stereo algorithms are united to apply to the stereo vision field.Design/methodology/approachLocal and DP stereo algorithms are used. Multi‐resolution images are obtained by pyramid algorithm and matching costs are gained by using eight‐stripe correlation window.FindingsThe time of disparity space image creation is greatly reduced because matching costs are computed by eight‐stripe window. Candidate ground control points (GCPs) are gained in the low‐resolution image. The total time of gaining GCPs is decreased in the extreme. Whole algorithm has a high matching‐rate and a fast speed.Research limitations/implicationsThe time of the whole algorithm is still a little bigger than local algorithm.Practical implicationsThe findings can be used in the stereo vision system equipped with planet vehicle.Originality/valueLocal and global stereo algorithms are united to apply to the stereo vision field. Matching costs are gained by using eight‐stripe correlation window.

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Development of an integrated sensor system for obstacle detection and terrain evaluation for application to unmanned ground vehicles

Cited by 7 publications

References 0 publications

Exploring Smart Environments Through Human Computation for Enhancing Blind Navigation

Exploring Smart Environments Through Human Computation for Enhancing Blind Navigation

Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming

Local‐global stereo matching algorithm

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