Search Results - "2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)"

Robust Dense Mapping for Large-Scale Dynamic Environments by Barsan, Ioan Andrei, Liu, Peidong, Pollefeys, Marc, Geiger, Andreas

“…We present a stereo-based dense mapping algorithm for large-scale dynamic urban environments. In contrast to other existing methods, we simultaneously…”
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A Flying Gripper Based on Cuboid Modular Robots by Gabrich, Bruno, Saldana, David, Kumar, Vijay, Yim, Mark

“…We present a novel flying modular platform capable of grasping and transporting objects. It is composed of four cooperative identical modules where each is…”
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Sim-to-Real Transfer of Robotic Control with Dynamics Randomization by Xue Bin Peng, Andrychowicz, Marcin, Zaremba, Wojciech, Abbeel, Pieter

“…Simulations are attractive environments for training agents as they provide an abundant source of data and alleviate certain safety concerns during the…”
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End-to-End Driving Via Conditional Imitation Learning by Codevilla, Felipe, Muller, Matthias, Lopez, Antonio, Koltun, Vladlen, Dosovitskiy, Alexey

“…Deep networks trained on demonstrations of human driving have learned to follow roads and avoid obstacles. However, driving policies trained via imitation…”
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Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning by Nagabandi, Anusha, Kahn, Gregory, Fearing, Ronald S., Levine, Sergey

“…Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large…”
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Overcoming Exploration in Reinforcement Learning with Demonstrations by Nair, Ashvin, McGrew, Bob, Andrychowicz, Marcin, Zaremba, Wojciech, Abbeel, Pieter

“…Exploration in environments with sparse rewards has been a persistent problem in reinforcement learning (RL). Many tasks are natural to specify with a sparse…”
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SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud by Wu, Bichen, Wan, Alvin, Yue, Xiangyu, Keutzer, Kurt

“…We address semantic segmentation of road-objects from 3D LiDAR point clouds. In particular, we wish to detect and categorize instances of interest, such as…”
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Time-Contrastive Networks: Self-Supervised Learning from Video by Sermanet, Pierre, Lynch, Corey, Chebotar, Yevgen, Hsu, Jasmine, Jang, Eric, Schaal, Stefan, Levine, Sergey, Brain, Google

“…We propose a self-supervised approach for learning representations and robotic behaviors entirely from unlabeled videos recorded from multiple viewpoints, and…”
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Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation by Tianhao Zhang, McCarthy, Zoe, Jow, Owen, Lee, Dennis, Xi Chen, Goldberg, Ken, Abbeel, Pieter

“…Imitation learning is a powerful paradigm for robot skill acquisition. However, obtaining demonstrations suitable for learning a policy that maps from raw…”
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Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching by Zeng, Andy, Shuran Song, Kuan-Ting Yu, Donlon, Elliott, Hogan, Francois R., Bauza, Maria, Daolin Ma, Taylor, Orion, Liu, Melody, Romo, Eudald, Fazeli, Nima, Alet, Ferran, Dafle, Nikhil Chavan, Holladay, Rachel, Morena, Isabella, Qu Nair, Prem, Green, Druck, Taylor, Ian, Liu, Weber, Funkhouser, Thomas, Rodriguez, Alberto

“…This paper presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key…”
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Social Attention: Modeling Attention in Human Crowds by Vemula, Anirudh, Muelling, Katharina, Oh, Jean

“…Robots that navigate through human crowds need to be able to plan safe, efficient, and human predictable trajectories. This is a particularly challenging…”
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UnDeepVO: Monocular Visual Odometry Through Unsupervised Deep Learning by Li, Ruihao, Wang, Sen, Long, Zhiqiang, Gu, Dongbing

“…We propose a novel monocular visual odometry (VO) system called UnDeepVO in this paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera and…”
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Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image by Fangchang Ma, Karaman, Sertac

“…We consider the problem of dense depth prediction from a sparse set of depth measurements and a single RGB image. Since depth estimation from monocular images…”
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Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning by Long, Pinxin, Fan, Tingxiang, Liao, Xinyi, Liu, Wenxi, Zhang, Hao, Pan, Jia

“…Developing a safe and efficient collision avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generates its…”
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Learning Sampling Distributions for Robot Motion Planning by Ichter, Brian, Harrison, James, Pavone, Marco

“…A defining feature of sampling-based motion planning is the reliance on an implicit representation of the state space, which is enabled by a set of probing…”
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A Benchmark Comparison of Monocular Visual-Inertial Odometry Algorithms for Flying Robots by Delmerico, Jeffrey, Scaramuzza, Davide

“…Flying robots require a combination of accuracy and low latency in their state estimation in order to achieve stable and robust flight. However, due to the…”
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IMLS-SLAM: Scan-to-Model Matching Based on 3D Data by Deschaud, Jean-Emmanuel

“…The Simultaneous Localization And Mapping (SLAM) problem has been well studied in the robotics community, especially using mono, stereo cameras or depth…”
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PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-Based Planning by Faust, Aleksandra, Oslund, Kenneth, Ramirez, Oscar, Francis, Anthony, Tapia, Lydia, Fiser, Marek, Davidson, James

“…We present PRM-RL, a hierarchical method for long-range navigation task completion that combines sampling-based path planning with reinforcement learning (RL)…”
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Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning by Isele, David, Rahimi, Reza, Cosgun, Akansel, Subramanian, Kaushik, Fujimura, Kikuo

“…Providing an efficient strategy to navigate safely through unsignaled intersections is a difficult task that requires determining the intent of other drivers…”
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Real-Time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs by Milioto, Andres, Lottes, Philipp, Stachniss, Cyrill

“…Precision farming robots, which target to reduce the amount of herbicides that need to be brought out in the fields, must have the ability to identify crops…”
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