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Supernumerary Robotic Limbs (SRLs) exhibit inherently compliant behavior due to the elasticity present at the intersection of human tissue and the robot. This compliance, can prominently influence the operation of some SRLs, depending on the application. In order to control the residual vibrations of SRLs, we have used an input-shaping method which is a computationally inexpensive approach. The effectiveness of this method in controlling the residual vibrations of a SRL has been proven using robustness analysis. User studies show that reducing the vibrations using input shaping directly increases the user satisfaction and comfort by at least 9%. It is also observed that 36% of the users preferred unshaped commands. We hypothesize that the shaped commands put a higher cognitive load on the user compared to unshaped commands. This shows that when dealing with human-robot interaction, user satisfaction becomes an equally important parameter as traditional performance criteria and should be taken into account while evaluating the success of any vibration-control method.

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Quantitative understanding of the human neuromotor system is essential for the implementation of the future robotic therapeutic exercises. For this purpose, sensorimotor adaptations in voluntary and involuntary movements facilitated by peripheral stimulation and resultant motor-evoked potentials (MEP) must be well characterized. One such facilitation exercise is paired associative stimulation (PAS). However, effective inter-stimulus intervals between cortical and peripheral stimulations are highly variable between individuals due to different physiological characteristics. Past studies measured MEPs in a wide range of time by incrementally varying inter-stimulus intervals to find the optimal interval in a specific subject, which has been a time-consuming process. This paper develops a search algorithm based on particle filtering to estimate individualized inter-stimulus intervals for PAS with mechanical muscle tendon stimulation realized by a pneumatically-operated robotic neuromodulatory system. The particle filter-based method reduces the number of PAS trials 70%–80% in comparison to the conventional incremental method. An accelerometer attached to the robotic system that measures exact timings of tendon stimulation can further reduce the number of trials.

In this case study we report on the use of a Next Generation Science Standards (NGSS)-aligned form of Structure-Behavior-Function, called Structure-Function-Mechanism (SFM), to teach four high school engineering teachers an approach for Biologically Inspired Design (BID). Functional theories of design describe a natural way in which designers solve design problems. They provide support for case-based and analogical-based reasoning systems and have been used successfully to teach BID to undergraduate students. We found that teachers instructed on BID practice and pedagogy using our modified theory were able to grasp the structural concepts and looked for clear markers separating mechanism (behavior) and function. Because of the systems-of-systems nature of most biological entities, these boundaries were often subjective, presenting unique challenge to teachers. As high school engineering teachers look for methods to enhance their pedagogy and to understand multidisciplinary content, these findings will inform future curriculum development and professional learning approaches for engineering education.