Self-Organizing Fuzzy Haptic Teleoperation of Mobile Robot Using Sparse Sonar Data

Abstract

Mobile robot teleoperation has been used in many areas of industrial automation, such as explosives disposal, nuclear waste manipulation, freight handling, or transportation. Here, the commonly provided audio-visual feedback often resulted in an inadequate perception of the remote environment. Haptic augmentation was shown to improve and positively enhance the control of the mobile robot. This paper presents novel self-organizing fuzzy adaptive mapping algorithm (SOFAMap) for a haptic teleoperation of mobile robots. The SOFAMap algorithm was specifically developed for a mobile robot with a rotational sonar sensory system, constituting an alternative to a traditionally used multisonar array. The main contributions of this paper are the following: 1) development of a specific self-organizing environment mapping structure inspired by the growing neural gas algorithm; 2) incorporating a fuzzy controller into the algorithm to adapt to robot's motion; and 3) resolving typical issues such as sensor noise, communication time delay, and low sampling rate. The experimental testing was performed in both virtual environment and on a real robotic platform, consisting of a Lego NXT mobile robot and a Novint Falcon 3-DOF haptic interface. The results showed that a high-fidelity haptic feedback can be successfully generated using a simpler and more affordable rotational sonar sensory system, as opposed to the typical multisonar array. Furthermore, it was demonstrated that the SOFAMap algorithm improves the operator's awareness of unstructured environments, making it applicable to wide range of mobile robot teleoperation systems.