Abstract
Humanoid robots provide many advantages when working together with humans to perform various tasks. Since humans in general have alot of experience in physically collaborating with each other, a humanoid with a similar range of motion and sensing has the potential to do the same.This thesis is focused on enabling humanoids that can do such tasks together withhumans: collaborative humanoids. In particular, we use the example where a humanoid and a human collaboratively carry and transport objectstogether. However, there is much to be done in order to achieve this. Here, we first focus on utilizing vision and haptic information together forenabling better collaboration. More specifically the use of vision-based control together with admittance control is tested as a framework forenabling the humanoid to better collaborate by having its own notion of the task. Next, we detail how walking pattern generators can be designedtaking into account physical collaboration. For this, we create leader and follower type walking pattern generators. Finally,the task of collaboratively carrying an object together with a human is broken down and implemented within an optimization-based whole-bodycontrol framework.