Search Results - "Deep Learning in Robotics and Automation"

Safe Control With Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction Methods for Robotics and Control by Dawson, Charles, Gao, Sicun, Fan, Chuchu

“…Learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at…”
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Deep Learning Approaches to Grasp Synthesis: A Review by Newbury, Rhys, Gu, Morris, Chumbley, Lachlan, Mousavian, Arsalan, Eppner, Clemens, Leitner, Jurgen, Bohg, Jeannette, Morales, Antonio, Asfour, Tamim, Kragic, Danica, Fox, Dieter, Cosgun, Akansel

“…Grasping is the process of picking up an object by applying forces and torques at a set of contacts. Recent advances in deep learning methods have allowed…”
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A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-Based Variational Autoencoder by Daehyung Park, Hoshi, Yuuna, Kemp, Charles C.

“…The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation. Multimodal sensory signals can be helpful for…”
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DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles by Xie, Zhanteng, Dames, Philip

“…This article proposes a novel learning-based control policy with strong generalizability to new environments that enables a mobile robot to navigate…”
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Motion Planning Networks: Bridging the Gap Between Learning-Based and Classical Motion Planners by Qureshi, Ahmed Hussain, Miao, Yinglong, Simeonov, Anthony, Yip, Michael C.

“…This article describes motion planning networks (MPNet), a computationally efficient, learning-based neural planner for solving motion planning problems.MPNet…”
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What the Constant Velocity Model Can Teach Us About Pedestrian Motion Prediction by Scholler, Christoph, Aravantinos, Vincent, Lay, Florian, Knoll, Alois

“…Pedestrian motion prediction is a fundamental task for autonomous robots and vehicles to operate safely. In recent years many complex approaches based on…”
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Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks by Lee, Michelle A., Zhu, Yuke, Zachares, Peter, Tan, Matthew, Srinivasan, Krishnan, Savarese, Silvio, Fei-Fei, Li, Garg, Animesh, Bohg, Jeannette

“…Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback. It is nontrivial to manually design a robot…”
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Flow: A Modular Learning Framework for Mixed Autonomy Traffic by Wu, Cathy, Kreidieh, Abdul Rahman, Parvate, Kanaad, Vinitsky, Eugene, Bayen, Alexandre M.

“…The rapid development of autonomous vehicles (AVs) holds vast potential for transportation systems through improved safety, efficiency, and access to mobility…”
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RLOC: Terrain-Aware Legged Locomotion Using Reinforcement Learning and Optimal Control by Gangapurwala, Siddhant, Geisert, Mathieu, Orsolino, Romeo, Fallon, Maurice, Havoutis, Ioannis

“…We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize…”
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Towards Generalization in Target-Driven Visual Navigation by Using Deep Reinforcement Learning by Devo, Alessandro, Mezzetti, Giacomo, Costante, Gabriele, Fravolini, Mario L., Valigi, Paolo

“…Among the main challenges in robotics, target-driven visual navigation has gained increasing interest in recent years. In this task, an agent has to navigate…”
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Cat-Like Jumping and Landing of Legged Robots in Low Gravity Using Deep Reinforcement Learning by Rudin, Nikita, Kolvenbach, Hendrik, Tsounis, Vassilios, Hutter, Marco

“…In this article, we show that learned policies can be applied to solve legged locomotion control tasks with extensive flight phases, such as those encountered…”
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RLBench: The Robot Learning Benchmark & Learning Environment by James, Stephen, Ma, Zicong, Arrojo, David Rovick, Davison, Andrew J.

“…We present a challenging new benchmark and learning-environment for robot learning: RLBench. The benchmark features 100 completely unique, hand-designed tasks,…”
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DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation by Lambeta, Mike, Chou, Po-Wei, Tian, Stephen, Yang, Brian, Maloon, Benjamin, Most, Victoria Rose, Stroud, Dave, Santos, Raymond, Byagowi, Ahmad, Kammerer, Gregg, Jayaraman, Dinesh, Calandra, Roberto

“…Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that…”
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Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments by Niroui, Farzad, Kaicheng Zhang, Kashino, Zendai, Nejat, Goldie

“…Rescue robots can be used in urban search and rescue (USAR) applications to perform the important task of exploring unknown cluttered environments. Due to the…”
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More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch by Calandra, Roberto, Owens, Andrew, Jayaraman, Dinesh, Lin, Justin, Wenzhen Yuan, Malik, Jitendra, Adelson, Edward H., Levine, Sergey

“…For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on…”
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DeepGait: Planning and Control of Quadrupedal Gaits Using Deep Reinforcement Learning by Tsounis, Vassilios, Alge, Mitja, Lee, Joonho, Farshidian, Farbod, Hutter, Marco

“…This letter addresses the problem of legged locomotion in non-flat terrain. As legged robots such as quadrupeds are to be deployed in terrains with geometries…”
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Learning Robust Control Policies for End-to-End Autonomous Driving From Data-Driven Simulation by Amini, Alexander, Gilitschenski, Igor, Phillips, Jacob, Moseyko, Julia, Banerjee, Rohan, Karaman, Sertac, Rus, Daniela

“…In this work, we present a data-driven simulation and training engine capable of learning end-to-end autonomous vehicle control policies using only sparse…”
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Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments by Xia, Fei, Shen, William B., Li, Chengshu, Kasimbeg, Priya, Tchapmi, Micael Edmond, Toshev, Alexander, Martin-Martin, Roberto, Savarese, Silvio

“…We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation solutions. Interactive Navigation…”
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Deep Neural Network Based Electrical Impedance Tomographic Sensing Methodology for Large-Area Robotic Tactile Sensing by Park, Hyunkyu, Park, Kyungseo, Mo, Sangwoo, Kim, Jung

“…Electrical impedance tomography (EIT) based tactile sensor offers significant benefits on practical deployment because of its sparse electrode allocation,…”
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Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model by Ty Nguyen, Chen, Steven W., Shivakumar, Shreyas S., Taylor, Camillo Jose, Kumar, Vijay

“…Homography estimation between multiple aerial images can provide relative pose estimation for collaborative autonomous exploration and monitoring. The usage on…”
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