mlsanityData to 14 Oct 2026

Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning

arXiv 2011.06192 ↗First posted 12 Nov 2020cs.RO cs.LGcited by 11

On the map: Offline RL and imitation learning from data → Robot manipulation imitation learning

Abstract (arXiv)

Robots that can execute various tasks automatically on behalf of humans are becoming an increasingly important focus of research in the field of robotics. Imitation learning has been studied as an efficient and high-performance method, and imitation learning based on bilateral control has been proposed as a method that can realize fast motion. However, because this method cannot implement autoregressive learning, this method may not generate desirable long-term behavior. Therefore, in this paper, we propose a method of autoregressive learning for bilateral control-based imitation learning. A new neural network model for implementing autoregressive learning is proposed. In this study, three types of experiments are conducted to verify the effectiveness of the proposed method. The performance is improved compared to conventional approaches; the proposed method has the highest rate of success. Owing to the structure and autoregressive learning of the proposed model, the proposed method can generate the desirable motion for successful tasks and have a high generalization ability for environmental changes.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data. Builds on 17 of its 46 references that are in the map. First posted on arXiv 12 Nov 2020.

Builds on

17 of 46 references.

Closest ancestors · 1

Same direction, newest first

  1. 2019Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning25 Oct

Other references · 16

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2015Scheduled Sampling for Sequence Prediction with Recurrent Neural Networkscited by 803
  4. 2015Sequence Level Training with Recurrent Neural Networkscited by 576
  5. 2016Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collectioncited by 316
  6. 2017Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperationcited by 289
  7. 2016Professor Forcing: A New Algorithm for Training Recurrent Networkscited by 216
  8. 2016Learning to Poke by Poking: Experiential Learning of Intuitive Physicscited by 154
  9. 2018One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learningcited by 148
  10. 2019Bridging the Gap between Training and Inference for Neural Machine Translationcited by 123
  11. 2019A Survey of Deep Learning-based Object Detectioncited by 106
  12. 2017Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstrationcited by 100
4 more
  1. 2018Imitation Learning for Object Manipulation Based on Position/Force Information Using Bilateral Controlcited by 21
  2. 2018Cross-Database Micro-Expression Recognition: A Benchmarkcited by 9
  3. 2019Rethinking Exposure Bias In Language Modelingcited by 9
  4. 2018Deep Learning Scooping Motion using Bilateral Teleoperationscited by 4

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 2; 2023: 0; 2024: 3; 2025: 2.

11 papers.

  1. 2024Bi-ACT: Bilateral Control-Based Imitation Learning via Action Chunking with Transformercited by 27
  2. 2021Imitation Learning for Variable Speed Contact Motion for Operation up to Control Bandwidthcited by 16
  3. 2024Tri-Modal Motion Retrieval by Learning a Joint Embedding Spacecited by 16
  4. 2022An Independently Learnable Hierarchical Model for Bilateral Control-Based Imitation Learning Applicationscited by 14
  5. 2022Imitation Learning for Nonprehensile Manipulation through Self-Supervised Learning Considering Motion Speedcited by 14
  6. 2024ILBiT: Imitation Learning for Robot Using Position and Torque Information based on Bilateral Control with Transformercited by 10
  7. 2021A New Autoregressive Neural Network Model with Command Compensation for Imitation Learning Based on Bilateral Controlcited by 5
  8. 2021Imitation learning for variable speed motion generation over multiple actionscited by 3
  9. 2025MaskPlanner: Learning-Based Object-Centric Motion Generation from 3D Point Cloudscited by 3
  10. 2025Temporal horizons in forecasting: a performance-learnability trade-offcited by 1
  11. 2021Bilateral Control-Based Imitation Learning for Velocity-Controlled Robotcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Imitation Learning from Observations: An Autoregressive Mixture of Experts Approach
  2. 2026Hierarchical Proportion Models for Motion Generation via Integration of Motion Primitives
  3. 2023End-to-End Stable Imitation Learning via Autonomous Neural Dynamic Policies
  4. 2024Fusion Dynamical Systems with Machine Learning in Imitation Learning: A Comprehensive Overview
  5. 2019Imitation Learning Based on Bilateral Control for Human-Robot Cooperation
  6. 2024Proleptic Temporal Ensemble for Improving the Speed of Robot Tasks Generated by Imitation Learning
  7. 2025Quantization-Free Autoregressive Action Transformer
  8. 2021CRIL: Continual Robot Imitation Learning via Generative and Prediction Model