mlsanityData to 7 Oct 2026

CasIL: Cognizing and Imitating Skills via a Dual Cognition-Action Architecture

arXiv 2309.16299 ↗First posted 28 Sep 2023cs.RO cs.HC cs.LGcited by 0

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

Abstract (arXiv)

Enabling robots to effectively imitate expert skills in longhorizon tasks such as locomotion, manipulation, and more, poses a long-standing challenge. Existing imitation learning (IL) approaches for robots still grapple with sub-optimal performance in complex tasks. In this paper, we consider how this challenge can be addressed within the human cognitive priors. Heuristically, we extend the usual notion of action to a dual Cognition (high-level)-Action (low-level) architecture by introducing intuitive human cognitive priors, and propose a novel skill IL framework through human-robot interaction, called Cognition-Action-based Skill Imitation Learning (CasIL), for the robotic agent to effectively cognize and imitate the critical skills from raw visual demonstrations. CasIL enables both cognition and action imitation, while high-level skill cognition explicitly guides low-level primitive actions, providing robustness and reliability to the entire skill IL process. We evaluated our method on MuJoCo and RLBench benchmarks, as well as on the obstacle avoidance and point-goal navigation tasks for quadrupedal robot locomotion. Experimental results show that our CasIL consistently achieves competitive and robust skill imitation capability compared to other counterparts in a variety of long-horizon robotic tasks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data. Builds on 28 of its 50 references that are in the map. First posted on arXiv 28 Sep 2023.

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28 of 50 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning30 May
  2. 2021Explainable Hierarchical Imitation Learning for Robotic Drink Pouring16 May
  3. 2020Visual Imitation Made Easy11 Aug

Other references · 25

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  4. 2017Proximal Policy Optimization Algorithmscited by 14,441
  5. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  6. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,286
  7. 2016OpenAI Gymcited by 1,684
  8. 2016Generative Adversarial Imitation Learningcited by 1,576
  9. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,528
  10. 2016End to End Learning for Self-Driving Carscited by 1,000
  11. 2019RLBench: The Robot Learning Benchmark & Learning Environmentcited by 669
  12. 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 601
13 more
  1. 2017One-Shot Visual Imitation Learning via Meta-Learningcited by 225
  2. 2020Accelerating Reinforcement Learning with Learned Skill Priorscited by 220
  3. 2018Neural probabilistic motor primitives for humanoid controlcited by 96
  4. 2018Hierarchical Imitation and Reinforcement Learningcited by 88
  5. 2021Demonstration-Guided Reinforcement Learning with Learned Skillscited by 73
  6. 2022Interactive Imitation Learning in Robotics: A Surveycited by 51
  7. 2017OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learningcited by 40
  8. 2016Learning Dexterous Manipulation Policies from Experience and Imitationcited by 32
  9. 2021Adversarial Option-Aware Hierarchical Imitation Learningcited by 19
  10. 2022Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Controlcited by 16
  11. 2023Primitive Skill-based Robot Learning from Human Evaluative Feedbackcited by 15
  12. 2020Provable Hierarchical Imitation Learning via EMcited by 10
  13. 2022Learning to Walk by Steering: Perceptive Quadrupedal Locomotion in Dynamic Environmentscited by 7

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  1. 2022Learning and Retrieval from Prior Data for Skill-based Imitation Learning
  2. 2022SKILL-IL: Disentangling Skill and Knowledge in Multitask Imitation Learning
  3. 2026Dual-Process Atomic Skill Learning: Decoupling Semantic Reasoning and Real-Time Control
  4. 2024Robotic Imitation of Human Actions
  5. 2024The intrinsic motivation of reinforcement and imitation learning for sequential tasks
  6. 2025REFLEX: Metacognitive Reasoning for Reflective Zero-Shot Robotic Planning with Large Language Models
  7. 2021Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation
  8. 2025SPECI: Skill Prompts based Hierarchical Continual Imitation Learning for Robot Manipulation