Interactive Robot Learning for Multimodal Emotion Recognition

A comprehensive survey of reinforcement learning for robot behavior. Weighs model-based against model-free methods and highlights the key challenges and successes.

Jens Kober J. Andrew Bagnell and Jan Peters

University lecture notes that teach machine learning through hands-on robotics. A course-length resource linking ML theory to real robot experiments.

Thomas P. Trappenberg

Presents a neural network approach to mobile robot navigation with a focus on obstacle avoidance. Learns motion decisions from human choices in varied situations.

Yiyang Chen, Chuanxin Cheng, Yueyuan Zhang, Xinlin Li and Lining Sun

Introduces machine learning to young students through robots and playful, hands-on activities. Uses a neural network playground to make the ideas tangible.

Viktoriya Olari, Kostadin Cvejoski and Oyvind Eide