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Reinforcement learning can enable robots to navigate to distant goals while optimizing user-specified reward functions, including preferences for following lanes, staying on paved paths, or avoiding freshly mowed grass.
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Self-Supervised Deep RL with Generalized Computation Graphs for Robot Navigation
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N. Savinov, A. Dosovitskiy, and V. Koltun · 2018
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PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-Based Planning
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Real-time information-theoretic exploration with gaussian mixture model maps
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W. Tabib, K. Goel, J. Yao, M. Dabhi, C. Boirum, and N. Michael · 2019
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gradslam: Dense SLAM meets automatic differentiation
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Efficient autonomous exploration planning of large-scale 3-d environments
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Habitat: A Platform for Embodied AI Research
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AI2-THOR: An Interactive 3D Environment for Visual AI
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Off-policy deep reinforcement learning without exploration
S. Fujimoto, D. Meger, and D. Precup · 2019
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S. Nasiriany, V. Pong, S. Lin, and S. Levine · 2019
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Rewriting history with inverse rl: Hindsight inference for policy improvement
B. Eysenbach, X. Geng, S. Levine, and R. R. Salakhutdinov · 2020
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Offline reinforcement learning with implicit q-learning
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D. Shah, B. Eysenbach, N. Rhinehart, and S. Levine · 2021
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Active mapping and robot exploration: A survey
I. Lluvia, E. Lazkano, and A. Ansuategi · 2021
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Offline reinforcement learning with fisher divergence critic regularization
I. Kostrikov, R. Fergus, J. Tompson, and O. Nachum · 2021
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Mt-opt: Continuous multi-task robotic reinforcement learning at scale
D. Kalashnikov, J. Varley, Y. Chebotar, B. Swanson, R. Jonschkowski, C. Finn, S. Levine, and K. Hausman · 2021
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Beyond pick-and-place: Tackling robotic stacking of diverse shapes
A. X. Lee, C. M. Devin, Y. Zhou, T. Lampe, K. Bousmalis, J. T. Springenberg, A. Byravan, A. Abdolmaleki, N. Gileadi, D. Khosid, et al · 2021
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Actionable models: Unsupervised offline reinforcement learning of robotic skills
Y. Chebotar, K. Hausman, Y. Lu, T. Xiao, D. Kalashnikov, J. Varley, A. Irpan, B. Eysenbach, R. Julian, C. Finn, and S. Levine · 2021
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Decision transformer: Reinforcement learning via sequence modeling
L. Chen, K. Lu, A. Rajeswaran, K. Lee, A. Grover, M. Laskin, P. Abbeel, A. Srinivas, and I. Mordatch · 2021
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