The limits and potentials of deep learning for robotics

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

(2016) Fayao Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

(2016) Cesar Cadena et al.   IEEE Transactions on Robotics

Learning state representations with robotic priors

(2015) Rico Jonschkowski et al.   AUTONOMOUS ROBOTS

Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot

(2015) Scott Kuindersma et al.   AUTONOMOUS ROBOTS

Visual Domain Adaptation: A survey of recent advances

(2015) Vishal M Patel et al.   IEEE SIGNAL PROCESSING MAGAZINE

Human-level concept learning through probabilistic program induction

(2015) B. M. Lake et al.   SCIENCE

Neural Networks and Neuroscience-Inspired Computer Vision

(2014) David Daniel Cox et al.   CURRENT BIOLOGY

Perceptual Annotation: Measuring Human Vision to Improve Computer Vision

(2014) Walter J. Scheirer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Probability Models for Open Set Recognition

(2014) Walter J. Scheirer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Nonmyopic View Planning for Active Object Classification and Pose Estimation

(2014) Nikolay Atanasov et al.   IEEE Transactions on Robotics

Simulation as an engine of physical scene understanding

(2013) P. W. Battaglia et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Toward Open Set Recognition

(2012) W. J. Scheirer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

On reverse engineering in the cognitive and brain sciences

(2012) Andreas Schierwagen   Natural Computing

iSAM2: Incremental smoothing and mapping using the Bayes tree

(2011) Michael Kaess et al.   INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH