Eye-in-hand/eye-to-hand configuration for a WMRA control based on visual servoing

Abstract

People suffering from severe disability like spinal cord injury dysfunctions are unable to control a wheelchair via a common joystick interface. For this target group we have developed a robotic wheelchair able to perform autonomous navigation and operate on different driving modes depending on the disability type of its user. Moreover, a 7-DoF wheelchair - mounted robotic arm (WMRA) was added to the 2-DoF nonholonomic wheelchair platform. In this paper, an image - based visual servoing (IBVS) approach is described with a Speeded Up Robust local Features detection (SURF) using eye-in-hand and eye-to-hand camera configuration for combined control of mobility and manipulation of the 9-DoF WMRA system to execute activities of daily living (ADL) autonomously. Selecting a control mode is done either by voice or by the touchscreen. Experiments with human users highlight advantages of augmentation in wheelchairs.