Unconventional computing devices are increasingly of interest as they can operate in environments hostile to silicon-based electronics, or compute in ways that traditional electronics cannot. Mechanical computers, wherein information processing is a material property emerging from the interaction of components with the environment, are one such class of devices. This information processing can be manifested in various physical substrates, one of which is granular matter. In a granular assembly, vibration can be treated as the information-bearing mode. This can be exploited to realize "polycomputing": materials can be evolved such that a single grain within them can report the result of multiple logical operations simultaneously at different frequencies, without recourse to quantum effects. Here, we demonstrate the evolution of a material in which one grain acts simultaneously as two different NAND gates at two different frequencies. NAND gates are of interest as any logical operations can be built from them. Moreover, they are nonlinear thus demonstrating a step toward general-purpose, computationally dense mechanical computers. Polycomputation was found to be distributed across each evolved material, suggesting the material's robustness. With recent advances in material sciences, hardware realization of these materials may eventually provide devices that challenge the computational density of traditional computers.

Digital signal processors are widely used in today's computers to perform advanced computational tasks. But, the selection of digital electronics as the physical substrate for computation a hundred years ago was influenced more by technological limitations than substrate appropriateness. In recent decades, advances in chemical, physical and material sciences have provided new options. Granular metamaterials are one such promising target for realizing mechanical computing devices. However, their high-dimensional design space and the unintuitive relationship between microstructure and desired macroscale behavior makes the inverse design problem formidable. In this paper, we use multiobjective evolutionary optimization to solve this inverse problem: we demonstrate the design of basic logic gates embedded in a granular metamaterial, and that the designed material can be "reprogrammed" via frequency modulation. As metamaterial design advances, more computationally dense materials may be evolved, amenable to reprogramming by increasingly sophisticated programming languages written in the frequency domain.

In this paper, we answer two interleaved questions. The first one is, having a redundant serial manipulator with a given cyclic task, how can we benefit simultaneously from both natural dynamics modification (NDM) and kinematic redundancy resolution to reduce the actuators' torque? Here, the NDM is done by devising parallel nonlinear monoarticular compliances (MACs), which span one joint, and nonlinear biarticular compliances (BACs), which pass over two joints. We take advantage of kinematic redundancy to exploit the robot's natural dynamics. The second question is how do kinematic redundancy resolution and the NDM interact to minimize the cost? To answer these questions, we cast the problem of simultaneous modification and exploitation of natural dynamics into a constrained multiobjective optimization problem. We show that the set of optimal compliances has an analytical solution as a parametric function of joint trajectories. Accordingly, we study how the components of cost function affect the profile of optimal compliant elements. The proposed method is implemented on a simulated planar 3-DoF manipulator and a simulated nonplanar 4-DoF manipulator for three different tasks. The results shed light on how kinematic redundancy resolution influences efficiency of using MACs and BACs and, consequently, increases attainable gains from the NDM. Moreover, analysis of the results specifies the roles of mono- and BACs and especially explains the reason behind the particular importance of having BACs to reduce the actuation cost.

We present a data-driven method for designing parallel compliance. Designing such compliance helps the system to improve energy efficiency, mainly by reducing negative work. The core idea is to design a controller first and then find springs working in parallel with each actuator such that force-displacement graph is lined up around displacement axis. By doing so, we simply shape the natural dynamics for performing the task efficiently. Maximum torque reduction for actuators is a byproduct of this design method. The method can be used in different cyclic robotic application, especially in legged locomotion systems. In this paper, we design a spinal compliance for a bounding quadruped robot in Webots. The results show that the power consumption and the maximum torque are reduced significantly.