Team Cornell's Skynet: Robust perception and planning in an urban environment

By Isaac Miller, Mark E. Campbell, Dan Huttenlocher, Frank-Robert Kline, Aaron Nathan, Sergei Lupashin, Jason Catlin, B. Schimpf, Pete Moran, Noah Zych and 3 more. 2008

161 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

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Citations in the corpus

Driving Policy Transfer via Modularity and Abstraction (2018, background): “ not validate their ideas with actual driving. Driving policies. Autonomous driving systems are commonly implemented via modular pipelines that comprise a multitude of carefully engineered components [14,26,33,49]. The advantage of this modular design is that each component can be developed in isola”
BADGR: An Autonomous Self-Supervised Learning-Based Navigation System (2020, background): “Autonomous mobile robot navigation has been extensively studied in many real-world scenarios, ranging from indoor navigation [2, 10, 11, 12] to outdoor driving [3, 13, 14, 15, 16].”
Message Passing Algorithms for Scalable Multitarget Tracking (2018, unknown): “Emerging MTT applications such as autonomous driving [13]–[15], indoor localization [16]–[18], robotic networks [19]–[21], and crowd counting [22]–[24] are especially challenging since they require real-time operation on resource-limited devices.”
The social dilemma of autonomous vehicles (2015, background): “ption of a safer technology. ∗ Correspondence should be addressed to irahwan@mit.edu The year 2007 saw the completion of the ﬁrst benchmark test for autonomous driving in realistic urban environments [1, 2]. Since then, Autonomous Vehicles (AVs) such as the Google Car covered thousands of miles of r”
Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving (2019, background): “Autonomous driving and ﬂight algorithms especially must work properly in a multi-agent environment [Urmson et al. , 2008; Kim and Shim, 2003], which requires us to craft adversarial situations for the tested algo-rithm by incorporating the interactions with other agents.”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, background): “The rule-based approach manually speciﬁes a driving action set for different driving context, mostly by the ﬁnite state machine (FSM) or similar frameworks like behavior trees [34], [349].”
Optimal trajectory generation for dynamic street scenarios in a Frenét Frame (2010, methodology): “Instead we add a certain safety distance to the size of our car on each side and make a hierarchical zero/one decision in terms of interference with other obstacles similar to [ 16 ].”
Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions (2015, background): “…used for on-road autonomous driving in the local search level is the one in which a search space contains a certain geometric curve (e.g. clothoids or splines) and several lateral shifts of this curve (e.g. Montemerlo et al., 2008; Urmson et al., 2008; Broggi et al., 2012; Ma et al., 2012).”