End-to-End Deep Imitation Learning: Robot Soccer Case Study
On the map: Offline RL and imitation learning from data → Robot manipulation imitation learning
Abstract (arXiv)
In imitation learning, behavior learning is generally done using the features extracted from the demonstration data. Recent deep learning algorithms enable the development of machine learning methods that can get high dimensional data as an input. In this work, we use imitation learning to teach the robot to dribble the ball to the goal. We use B-Human robot software to collect demonstration data and a deep convolutional network to represent the policies. We use top and bottom camera images of the robot as input and speed commands as outputs. The CNN policy learns the mapping between the series of images and speed commands. In 3D realistic robotics simulator experiments, we show that the robot is able to learn to search the ball and dribble the ball, but it struggles to align to the goal. The best-proposed policy model learns to score 4 goals out of 20 test episodes.
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 3 of its 20 references that are in the map. First posted on arXiv 28 Jun 2018.
Builds on
3 of 20 references.
References · 3
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
- 2015End-to-End Training of Deep Visuomotor Policiescited by 847
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- 2022GoalsEye: Learning High Speed Precision Table Tennis on a Physical Robot
- 2021MimicBot: Combining Imitation and Reinforcement Learning to win in Bot Bowl
- 2020Deep Reinforcement Learning with Mixed Convolutional Network
- 2024VITAL: Interactive Few-Shot Imitation Learning via Visual Human-in-the-Loop Corrections
- 2026Human-to-Robot Interaction: Learning from Video Demonstration for Robot Imitation
- 2022One-Shot Domain-Adaptive Imitation Learning via Progressive Learning