Reinforcement Learning Based Shared Control Navigation

Shared control is a mode where the user input is combined with a planned motion to achieve a common goal. In navigation, a shared control approach could provide a potential mobility solution for people who have a mobility impairment and find traditional powered wheelchairs unsuitable. While stateof-the-art work explored shared control navigation in simple environments, it is still challenging to solve for dynamic, crowded scenarios, in a way that is acceptable to users. Learning from recent advances in robot navigation, we present a reinforcement learning based framework, which allows navigation to be achieved in a shared controlled way. Our approach was trained and tested in a Unity3D based simulator. It achieved fewer collisions, comparable completion time and relatively high user agreement when compared with other state-of-the-art methods