Shared Control Templates for Assistive Robotics

Light-weight robotic manipulators can be used to restore the manipulation capability of people with a motor disability. However, manipulating the environment poses a complex task, especially when the control interface is of low bandwidth, as may be the case for users with impairments. Therefore, we propose a constraint-based shared control scheme to define skills which provide support during task execution. This is achieved by representing a skill as a sequence of states, with specific user command mappings and different sets of constraints being applied in each state. New skills are defined by combining different types of constraints and conditions for state transitions, in a human-readable format. We demonstrate its versatility in a pilot experiment with three activities of daily living. Results show that even complex, high-dimensional tasks can be performed with a low-dimensional interface using our shared control approach.

I. Introduction

The aim of assistive robotic arms is to restore manipulation capabilities of people with disabilities, thereby enabling them to perform tasks of daily living. An example is EDAN (EMG-controlled Daily AssistaNt), which consists of a DLR Light-Weight Robot III with a DLR-HIT hand, mounted on a power-wheelchair, see Fig. 1.a. Since goal-directed physical manipulation of the environment is often complex and intricate, controlling the robotic arm can be difficult, and may lead to a high cognitive workload. This is especially the case for mobile manipulation systems such as EDAN, as they have many degrees of freedom (DoFs) which all need to be controlled appropriately to achieve a task. For instance, opening and going through a door poses a real challenge, as grasping the handle is intricate, and opening the door requires the coordination of both arm and wheelchair movements [1].