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BAM! Base Abstracted Modeling with Universal Notice Network: Fast Skill Transfer Between Mobile Manipulators.

, , , and . CoDIT, page 926-932. IEEE, (2020)

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Task-Specific Loss: A Teacher-Centered Approach to Transfer Learning Between Distinctly Structured Robotic Agents., , , and . ICINCO (Selected Papers), volume 793 of Lecture Notes in Electrical Engineering, page 166-186. Springer, (2020)Robotic Control of the Deformation of Soft Linear Objects Using Deep Reinforcement Learning., , , , , and . CoRR, (2023)General Framework for the Optimization of the Human-Robot Collaboration Decision-Making Process Through the Ability to Change Performance Metrics., , , and . Frontiers Robotics AI, (2021)BAM! Base Abstracted Modeling with Universal Notice Network: Fast Skill Transfer Between Mobile Manipulators., , , and . CoDIT, page 926-932. IEEE, (2020)BSplines Properties with Interval Analysis for Constraint Satisfaction Problem: Application in Robotics., , , and . IAS, volume 867 of Advances in Intelligent Systems and Computing, page 490-503. Springer, (2018)Delay Aware Universal Notice Network: Real world multi-robot transfer learning., , , and . IROS, page 1251-1258. IEEE, (2021)Robotic Control of the Deformation of Soft Linear Objects Using Deep Reinforcement Learning., , , , , and . CASE, page 1516-1522. IEEE, (2022)Universal Notice Networks: Transferring Learned Skills Through a Broad Panel of Applications., , , and . J. Intell. Robotic Syst., 107 (2): 18 (February 2023)CoachGAN: Fast Adversarial Transfer Learning between Differently Shaped Entities., , , and . ICINCO, page 89-96. ScitePress, (2020)Optimal robot base placements for coverage tasks., , and . CASE, page 235-240. IEEE, (2018)