Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation

Autor: Ahmed Hussain Qureshi, Michael C. Yip, Mayur J. Bency

Publikováno v: IROS

Fast and efficient path generation is critical for robots operating in complex environments. This motion planning problem is often performed in a robot’s actuation or configuration space, where popular pathfinding methods such as A*, RRT*, get expo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c625f0bd1fd3243776afcbbdad07fa69
http://arxiv.org/abs/1904.11102

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Motion Planning Networks

Autor: Anthony Simeonov, Michael C. Yip, Ahmed Hussain Qureshi, Mayur J. Bency

Publikováno v: ICRA

Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics applications such as self-driving cars. Existing motion planning methods become ineffective as their computational complexity increases exponentially with th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02ca2fdaa6e9782961a62a3998443133

Beyond Spatial Auto-Regressive Models: Predicting Housing Prices with Satellite Imagery

Autor: Mudhakar Srivatsa, Raghu K. Ganti, Swati Rallapalli, Archith J. Bency, B.S. Manjunath

Publikováno v: WACV
Bency, AJ; Rallapalli, S; Ganti, RK; Srivatsa, M; & Manjunath, BS. (2017). Beyond Spatial Auto-Regressive Models: Predicting Housing Prices with Satellite Imagery. UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/77c0438f

When modeling geo-spatial data, it is critical to capture spatial correlations for achieving high accuracy. Spatial Auto-Regression (SAR) is a common tool used to model such data, where the spatial contiguity matrix (W) encodes the spatial correlatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ebf2f8c56306373eb302ed5370470a
https://doi.org/10.1109/wacv.2017.42

Search Tracker: Human-derived object tracking in-the-wild through large-scale search and retrieval

Autor: Archith J. Bency, B.S. Manjunath, Carter De Leo, S. Karthikeyan, Santhoshkumar Sunderrajan

Publikováno v: Bency, AJ; Karthikeyan, S; De Leo, C; Sunderrajan, S; & Manjunath, BS. (2017). Search Tracker: Human-Derived Object Tracking in the Wild Through Large-Scale Search and Retrieval. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 27(8), 1803-1814. doi: 10.1109/TCSVT.2016.2555718. UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/3r39r46k
IEEE Transactions on Circuits and Systems for Video Technology, vol 27, iss 8
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol 27, iss 8

Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter and occlusions. In this paper, we present a method to leverage human knowledge in the form of annotated video librar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff8c7e2c63f9cde91c2fcd107096847b
http://arxiv.org/abs/1602.01890