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Bioinspiration & Embodied Intelligence
The agile nature of physical interactions in animal and plant species has inspired many recent advances in robotics and their control frameworks. However, they still face challenges in interaction with ever-changing unconstructured world that we live in. Intelligence is one of nature's survival solutions for biological creatures to adapt to and reshape their surroundings. Our robots are no different in these remits. An important key to their survival and effectiveness in the natural world is the concept of Artificial Intelligence (AI). In this chapter we provide a brief overview of the rapidly emerging Soft Robotics research community around AI relevant concepts such as Embodied intelligence and Morphological Computation. More specifically, we focused on the importance of setting such "community goals" to create a diverse interdisciplinary research environment, an enormously important element to keep up with our rapidly progressing world. To this end, we focused on the collaborations within and between the communities, impacts of the recently established IEEE Soft Robotics Technical Committee on coordinating these efforts, and most important of all, the key ideas and perspectives based on 200 interviews with researchers across different fields.
This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that the whisker vibrations will have a dominant frequency at the vertical perturbation frequency of the mobile robot sandwiched by two other less dominant but distinct frequency components. These frequency components may come from bifurcation of vibration frequency due to nonlinear interaction dynamics at steady state. Experimental results also exhibit distinct dominant frequency components unique to the speed of the robot and the terrain roughness. This nonlinear dynamic feature is used in a deep multi-layer perceptron neural network to classify terrains. We achieved 85.6\% prediction success rate for seven flat terrain surfaces with different textures.
Mammals like rats, who live in dark burrows, heavily depend on tactile perception obtained through the vibrissal system to move through gaps and to discriminate textures. The organization of a mammalian whisker follicle contains multiple sensory receptors and glands strategically organized to capture tactile sensory stimuli of different frequencies. In this paper, we used a controllable stiffness soft robotic follicle to test the hypothesis that the multimodal sensory receptors together with the controllable stiffness tissues in the whisker follicle form a physical structure to maximize tactile information. In our design, the ring sinus and ringwulst of a biological follicle are represented by a linear actuator connected to a stiffness controllable mechanism in-between two different frequency-dependent data capturing modules. In this paper, we show for the first time the effect of the interplay between the stiffness and the speed of whisking on maximizing a difference metric for texture classification.
Spiders are able to extract crucial information, such as the location prey, predators, mates, and even broken threads from propagating web vibrations. The complex structure of the web suggests that the morphology itself might provide computational support in form of a mechanical signal processing system - often referred to as morphological computation. We present preliminary results on identifying these computational aspects in naturally spun webs. A recently presented definition for physical computational systems, consisting of three main elements: (i) a mathematical part, (ii) a computational setup with a theoretical and real part, and (iii) an interpretation, is employed for the first time, to characterize these morphological computation properties. Signal transmission properties of a real spider orb web, as the real part of a morphological computation setup, is investigated in response to step transverse inputs. The parameters of a lumped system model, as the theoretical part of a morphological computation setup, are identified empirically and with the help of an earlier FEM model for the same web. As the possible elements of a computational framework, the web transverse signal filtering, attenuation, delay, memory effect, and deformation modes are briefly discussed based on experimental data and numerical simulations.
We investigate how unmanned aerial vehicles (UAVs) with flexible wings can be designed to exploit the aeroelasticity of wing deformation that is present in bat wings, with a view to improve the efficiency of flight. We constructed a robotic bat wing with fully passive elastic wing-folding properties. The robotic wing is powered by a gearbox running two synchronised motors, effectively providing one degree of motion: the upstroke and down-stroke of the wing. Through numerical simulations and setup experiments, we observed that by integrating a span-wise elastic network into the bat wing, we were able to achieve passive wing-folding that mimics the 8-shape wing-folding seen in bats' high speed flight. This way, we were able to reduce the complexity and additional actuation associated with wing-folding in a robotic wing.