TerraMax: Team Oshkosh Urban Robot

Chen, Yiliang; Sundareswaran, V.; Craig, Anderson; Broggi, Alberto; Grisleri, Paolo; Pier, Paolo Porta; Zani, Paolo; Beck, J. Christopher

doi:10.1007/978-3-642-03991-1_14

Cited by 23 publications

(18 citation statements)

References 13 publications

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“…While a quantitative anlayisis of the quality of the generated depth maps is not easy to carry out, mainly because producing a reliable ground truth is not an easy task in outdoor environments, the extensive tests performed before and during the DARPA Grand Challenge 2005 [4] and the DARPA Urban Challenge [8] have shown that the proposed approaches provide an effective and reliable reconstruction of the vehicle surroundings.…”

Section: Discussionmentioning

confidence: 99%

Incremental disparity space image computation for automotive applications

Felisa

Zani

2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Generating a depth map from a pair of stereo images is a challenging task, which is often further complicated by the additional restrictions imposed by the target application; in the automotive field, for example, real-time environment reconstruction is essential for safety and autonomous navigation systems, thus requiring reduced processing times, often at the expense of a somewhat limited degree of accuracy in the results. Nevertheless, a-priori knowledge on the intended use of the algorithm can also be exploited to improve its performance, both in terms of precision and computational burden.This paper presents three different approaches to incremental Disparity Space Image (DSI) computation, which leverage the properties of a stereo-vision system installed on a vehicle to produce accurate depth maps at sustained frame rates on commodity hardware.

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Section: Discussionmentioning

confidence: 99%

Incremental disparity space image computation for automotive applications

Felisa

Zani

2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…Braid et al, 2006b) and the DARPA Urban Challenge (cfr. Chen et al, 2009). VisLab also equipped other intelligent vehicles such as ARGO, presented by Broggi et al (1999) and, more recently, BRAiVE (Bombini et al, 2009), as presented in Section 1.…”

Section: Vehicles Selectionmentioning

confidence: 99%

“…The DARPA Challenges (Ozguner et al, 2004;Braid et al, 2006a;Chen et al, 2008) were the most important events that pushed many research teams to build driverless vehicles and face real environments and real scenarios. In 2004In , 2005In and 2007, DARPA organised races amongst autonomous vehicles with different rules: in unknown off-road scenarios and in urban settings with other traffi c. Many teams fi elded successful entries in these events, progressing the overall knowledge in this fi eld.…”

Section: Introductionmentioning

confidence: 99%

The VisLab Intercontinental Autonomous Challenge: an extensive test for a platoon of intelligent vehicles

Broggi

Cerri

Felisa

et al. 2012

IJVAS

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This paper presents the VisLab Intercontinental Autonomous Challenge (VIAC), an autonomous vehicles test carried out from Parma to Shanghai between July and October 2010 by the VisLab team. The vehicle equipment is explained introducing the sensing systems which were tested during the journey. Trip details and the fi rst statistics are presented as well.Keywords: vehicle autonomous systems; platooning; computer vision.Reference to this paper should be made as follows: Broggi, A., Cerri, P., Felisa, M., Laghi, M.C., Mazzei, L. and Porta, P.P. 148A. Broggi et al.

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“…Reduced cost and size are also mandatory to allow straightforward integration and thus commercialization in the automotive market [2], [3]. On the other hand for autonomous vehicles, systems cost and size are currently less important but they have to deal with all weather conditions, all terrain, and all scenarios [4], [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Moving from analog to digital driving

Broggi

Debattisti

Panciroli

et al. 2013

2013 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-This paper presents a new vehicle guidance paradigm based on high level commands together with a new system architecture that can handle different levels of automation. First, an overview of different automation levels spanning from manual driving to fully autonomous driving is given, then a detailed description of the digital driving paradigm is also shown. This includes a detailed description of the maneuver level planner which is based on a new concept of planning based on checkpoints. Then, an overview of the new architecture is given, describing is key aspects. An analysis of the proposed paradigm, with the description of a preliminary tests in real scenarios concludes this paper.

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TerraMax: Team Oshkosh Urban Robot

Cited by 23 publications

References 13 publications

Incremental disparity space image computation for automotive applications

Incremental disparity space image computation for automotive applications

The VisLab Intercontinental Autonomous Challenge: an extensive test for a platoon of intelligent vehicles

Moving from analog to digital driving

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