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Naturalistic Robot Arm Trajectory Generation via Representation Learning

arXiv 2309.07550 ↗First posted 14 Sep 2023cs.RO cs.LGcited by 0

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Abstract (arXiv)

The integration of manipulator robots in household environments suggests a need for more predictable and human-like robot motion. This holds especially true for wheelchair-mounted assistive robots that can support the independence of people with paralysis. One method of generating naturalistic motion trajectories is via the imitation of human demonstrators. This paper explores a self-supervised imitation learning method using an autoregressive spatio-temporal graph neural network for an assistive drinking task. We address learning from diverse human motion trajectory data that were captured via wearable IMU sensors on a human arm as the action-free task demonstrations. Observed arm motion data from several participants is used to generate natural and functional drinking motion trajectories for a UR5e robot arm.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 14 Sep 2023.

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References · 3

  1. 2015Structural-RNN: Deep Learning on Spatio-Temporal Graphscited by 234
  2. 2020History Repeats Itself: Human Motion Prediction via Motion Attentioncited by 164
  3. 2021Space-Time-Separable Graph Convolutional Network for Pose Forecastingcited by 84

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  1. 2019Imitating by generating: deep generative models for imitation of interactive tasks
  2. 2025Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Survey
  3. 2022Interactive Imitation Learning of Bimanual Movement Primitives
  4. 2022Imitation Learning for Nonprehensile Manipulation through Self-Supervised Learning Considering Motion Speed
  5. 2025Towards Bio-Inspired Robotic Trajectory Planning via Self-Supervised RNN
  6. 2024Leveraging Pretrained Latent Representations for Few-Shot Imitation Learning on a Dexterous Robotic Hand
  7. 2026Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation
  8. 2021Learning to Share Autonomy Across Repeated Interaction