Significance: Folding DNA into complex 3D shapes (DNA origami) has emerged as a powerful method for the precise design and fabrication of self-assembled nanodevices. Current efforts have focused largely on developing static objects or structures with small movements and/or unspecified motion paths. Here we establish a basis for developing DNA-based nanomachines by creating dynamic mechanisms with well-defined motion. We demonstrate the design of nanoscale 1D, 2D, and 3D motion by integrating concepts from engineering machine design with DNA origami nanotechnology.

In this paper, a pseudorigid-body (PRB) 3R model, which consists of four rigid links joined by three revolute joints and three torsion springs, is proposed for approximating the deflection of a cantilever beam subject to a general tip load. The large deflection beam equations are solved through numerical integration. A comprehensive atlas of the tip deflection for various load modes is obtained. A three-dimensional search routine has been developed to find the optimal set of characteristic radius factors and spring stiffness of the PRB 3R model. Detailed error analysis has been done by comparing with the precomputed tip deflection atlas. Our results show that the approximation error is much less than that of the conventional PBR 1R model. To demonstrate the use of the PRB 3R model, a compliant four-bar linkage is studied and verified by a numerical example. The result shows a maximum tip deflection error of 1.2% compared with the finite element analysis model. The benefits of the PRB 3R model include that (a) the model parameters are independent of external loads, (b) the approximation error is relatively small for even large deflection beams, and (c) the derived kinematic and static constraint equations are simpler to solve compared with the finite element model.

This paper details the design and fabrication process of a fully integrated soft humanoid robotic hand with five finger that integrate an embedded shape memory alloy (SMA) actuator and a piezoelectric transducer (PZT) flexure sensor. Several challenges including precise control of the SMA actuator, improving power efficiency, and reducing actuation current and response time have been addressed. First, a Ni-Ti SMA strip is pretrained to a circular shape. Second, it is wrapped with a Ni-Cr resistance wire that is coated with thermally conductive and electrically isolating material. This design significantly reduces actuation current, improves circuit efficiency, and hence reduces response time and increases power efficiency. Third, an antagonistic SMA strip is used to improve the shape recovery rate. Fourth, the SMA actuator, the recovery SMA strip, and a flexure sensor are inserted into a 3D printed mold which is filled with silicon rubber materials. The flexure sensor feeds back the finger shape for precise control. Fifth, a demolding process yields a fully integrated multifunctional soft robotic finger. We also fabricated a hand assembled with five fingers and a palm. We measured its performance and specifications with experiments. We demonstrated its capability of grasping various kinds of regular or irregular objects. The soft robotic hand is very robust and has a large compliance, which makes it ideal for use in an unstructured environment. It is inherently safe to human operators as it can withstand large impacts and unintended contacts without causing any injury to human operators or damage to the environment.

Recent and future advances enabling the design of mechanical properties and dynamic behavior of DNA nanostructures will greatly expand the functional scope of DNA-based devices.

With the increase in driver assistance systems, driver models are becoming more important to vehicle control, driving safety, and performance. To make these driver assistance systems better cooperate with human drivers, the driver models need to be able to predict human driving behaviors and distinguish among different drivers. In this paper, a combined driver model consisting of a compensatory transfer function and an anticipatory component based on road geometry is integrated with the design of the individual driver's desired path. The proposed driver model parameters are obtained from human subject test data collected in a driving simulator. It has been shown that the proposed combined driver model is able to replicate each driver's steering wheel angle signals for a variety of maneuvers at different vehicle speeds. The driver model is then validated by first using a polynomial to interpolate the driver model and desired path parameters for an intermediate speed. It is also validated by comparing two different drivers' model parameter sets to show that each driver has a unique set of parameters. The final validation is to show that the proposed individual driver's desired path offers more accurate steering wheel fits than the previous geometric centerline.