No abstract

<p>Upper-limb exoskeletons (ULEs) have the potential to assist humans to accomplish tasks by distributing a heavy load. ULEs are designed to be comfortable and lightweight wearable robots which has resulted in complexity in their structures, actuators, and power transmissions. Additionally, different ULE vendor structures and biomechanical variations between humans resulted in dissimilar coordinated ULE systems. These complex multi-robot systems can be handled by adaptive virtual decomposition control (VDC) if unknown dynamic models are not considered. Hence, this paper proposes a new distributed framework for the adaptive impedance-based VDC method to the address abovementioned challenges and thereby enhance the system performance and robustness. To that end, the proposed control method has a prediction capability and an ancillary control law for coordinated dissimilar ULEs holding a common object. The system stability is analyzed using the input-to-state stability approach. For validation, the proposed control and a state-of-the-art adaptive VDC methods are implemented on a symmetric bimanual exoskeleton with seven degrees of freedom for each arm. Four bimanual task scenarios are performed with different internal arm forces and with/without an obstacle. The experimental results show the superiority of the proposed control method. </p>

<p>Upper-limb exoskeletons (ULEs) have the potential to assist humans to accomplish tasks by distributing a heavy load. ULEs are designed to be comfortable and lightweight wearable robots which has resulted in complexity in their structures, actuators, and power transmissions. Additionally, different ULE vendor structures and biomechanical variations between humans resulted in dissimilar coordinated ULE systems. These complex multi-robot systems can be handled by adaptive virtual decomposition control (VDC) if unknown dynamic models are not considered. Hence, this paper proposes a new distributed framework for the adaptive impedance-based VDC method to the address abovementioned challenges and thereby enhance the system performance and robustness. To that end, the proposed control method has a prediction capability and an ancillary control law for coordinated dissimilar ULEs holding a common object. The system stability is analyzed using the input-to-state stability approach. For validation, the proposed control and a state-of-the-art adaptive VDC methods are implemented on a symmetric bimanual exoskeleton with seven degrees of freedom for each arm. Four bimanual task scenarios are performed with different internal arm forces and with/without an obstacle. The experimental results show the superiority of the proposed control method. </p>