Human-to-Robot Imitation Learning: A Survey and Taxonomy of Methods (April 2026) logo

Human-to-Robot Imitation Learning: A Survey and Taxonomy of Methods (April 2026)

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Comprehensive survey of human-to-robot imitation learning — behavioral cloning, inverse reinforcement learning, adversarial imitation, and their combinations; includes taxonomy, benchmarks, and open challenges

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Open Source

About Human-to-Robot Imitation Learning: A Survey and Taxonomy of Methods (April 2026)

A comprehensive survey of human-to-robot imitation learning methods, covering behavioral cloning, inverse reinforcement learning, adversarial imitation, and their combinations. Includes a taxonomy of methods, benchmarks, and open challenges.

Key Features

Comprehensive taxonomy of imitation learning methods
Coverage of behavioral cloning, inverse reinforcement learning, adversarial imitation
Discussion of benchmarks and open challenges
Free open-access paper on arXiv

Pros & Cons

Pros
  • Free access on arXiv
  • Comprehensive and structured taxonomy
  • Covers multiple imitation learning paradigms
Cons
  • Not a software implementation, only a theoretical survey