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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. [ABSTRACT FROM PUBLISHER]

Recently, there has been a growing interest in using modular and reconfigurable robots (MRRs) in flexible automation to reduce labor and increase throughput. Moreover, the significant facilitation of repair and maintenance of MRRs has attracted manufacturers to respond to the increasing desire for new products and methods of production in today's competitive market. As a result, design and control of such systems have become major topics for investigation in recent years. This paper presents a novel design methodology of interval type-2 Takagi–Sugeno–Kang fuzzy logic controllers (IT2 TSK FLCs) for MRR manipulators with uncertain dynamic parameters. We develop a mathematical framework for the design of IT2 TSK FLCs for tracking purposes that can be effectively used in real-time applications. To verify the effectiveness of the proposed controller, experiments are performed on an MRR with two degrees of freedom, which exhibits dynamic coupling behavior. Results show that the developed controller can outperform some well-known linear and nonlinear controllers for different configurations. Therefore, the proposed structure can be adopted for the position control of MRRs with unknown dynamic parameters in trajectory-tracking applications. [ABSTRACT FROM AUTHOR]