Richard E. Groff

Towards a 3g crawling robot through the integration of microrobot technologies

This paper discusses the biomimetic design and assembly of a 3g self-contained crawling robot fabricated through the integrated use of various microrobot technologies. The hexapod structure is designed to move in an alternating tripod gait driven by two piezoelectric actuators connected by sliding plates to two sets of three legs. We present results of both the kinematic and static analyses of the driving mechanism that essentially consists of three slider cranks in series. This analysis confirmed the force differential needed to propel the device. We then review various other microrobot technologies that have been developed including actuator design and fabrication, power and control electronics design, programming via a finite state machine, and the development of bioinspired fiber arrays. These technologies were then successfully integrated into the device. The robot is now functioning and we have already fabricated three iterations of the proposed device. We hope with further design iterations to produce a fully operational model in the near future

Effective elastic modulus of isolated gecko setal arrays

SUMMARY Conventional pressure sensitive adhesives (PSAs) are fabricated from soft viscoelastic materials that satisfy Dahlquists criterion for tack with a Youngs modulus (E) of 100 kPa or less at room temperature and 1 Hz. In contrast, the adhesive on the toes of geckos is made of β-keratin, a stiff material with E at least four orders of magnitude greater than the upper limit of Dahlquists criterion. Therefore, one would not expect aβ -keratin structure to function as a PSA by deforming readily to make intimate molecular contact with a variety of surface profiles. However, since the gecko adhesive is a microstructure in the form of an array of millions of high aspect ratio shafts (setae), the effective elastic modulus (Eeff) is much lower than E of bulkβ -keratin. In the first test of the Eeff of a gecko setal adhesive, we measured the forces resulting from deformation of isolated arrays of tokay gecko (Gekko gecko) setae during vertical compression, and during tangential compression at angles of +45° and -45°. We tested the hypothesis that Eeff of gecko setae falls within Dahlquists criterion for tack, and evaluated the validity of a model of setae as cantilever beams. Highly linear forces of deformation under all compression conditions support the cantilever model. Eeff of setal arrays during vertical and +45° compression (along the natural path of drag of the setae) were 83±4.0 kPa and 86±4.4 kPa (means ± s.e.m.), respectively. Consistent with the predictions of the cantilever model, setae became significantly stiffer when compressed against the natural path of drag: Eeff during -45° compression was 110±4.7 kPa. Unlike synthetic PSAs, setal arrays act as Hookean elastic solids; setal arrays function as a bed of springs with a directional stiffness, assisting alignment of the adhesive spatular tips with the contact surface during shear loading.

Automated gait adaptation for legged robots

Gait parameter adaptation on a physical robot is an error-prone, tedious and time-consuming process. In this paper we present a system for gait adaptation in our RHex series of hexapedal robots that renders this arduous process nearly autonomous. The robot adapts its gait parameters by recourse to a modified version of Nelder-Mead descent, while managing its self-experiments and measuring the outcome by visual servoing within a partially engineered environment The resulting performance gains extend considerably beyond what we have managed with hand tuning. For example, the best hand tuned alternating tripod gaits never exceeded 0.8 m/s nor achieved specific resistance below 2.0. In contrast, Nelder-Mead based tuning has yielded alternating tripod gaits at 2.7 m/s (well over 5 body lengths per second) and reduced specific resistance to 0.6 while requiring little human intervention at low and moderate speeds. Comparable gains have been achieved on the much larger ruggedized version of this machine.

Robotics in scansorial environments

We review a large multidisciplinary effort to develop a family of autonomous robots capable of rapid, agile maneuvers in and around natural and artificial vertical terrains such as walls, cliffs, caves, trees and rubble. Our robot designs are inspired by (but not direct copies of) biological climbers such as cockroaches, geckos, and squirrels. We are incorporating advanced materials (e.g., synthetic gecko hairs) into these designs and fabricating them using state of the art rapid prototyping techniques (e.g., shape deposition manufacturing) that permit multiple iterations of design and testing with an effective integration path for the novel materials and components. We are developing novel motion control techniques to support dexterous climbing behaviors that are inspired by neuroethological studies of animals and descended from earlier frameworks that have proven analytically tractable and empirically sound. Our near term behavioral targets call for vertical climbing on soft (e.g., bark) or rough surfaces and for ascents on smooth, hard steep inclines (e.g., 60 degree slopes on metal or glass sheets) at one body length per second.

Attachment of fiber array adhesive through side contact

Very slender cylindrical fibers are capable of bending over and maintaining side contact with an opposing substrate even as the fibers are pulled away, providing a mode of adhesion for fiber array adhesives. This paper analyzes side contact and its effect on normal adhesion and provides guidelines for fiber length to achieve side contact under zero load as a function of elastic modulus, area moment of inertia, initial geometry, and energy of adhesion between fiber and substrate. Numerical results for several relevant geometries are presented as well as a comparison to recently reported normal adhesion measurements of multiwalled carbon nanotube arrays.

CLUMPING AND PACKING OF HAIR ARRAYS MANUFACTURED BY NANOCASTING

The gecko’s remarkable dry adhesive system, consisting of arrays of heirarchically stuctured hairs made from a stiff material, has motivated widespread interest in creating a synthetic dry adhesive whose adhesive properties derive more from its geometry than its bulk material properties. Recently, methods for synthesizing simple hair arrays have been developed. It has been observed that micro and nanosized synthetic hairs often adhere together to form clumps. This paper introduces several models and guidelines for predicting clumping conditions through hair geometry and lattice structure, and presents our methods for casting hair arrays.

A rapidly prototyped 2-axis positioning stage for microassembly using large displacement compliant mechanisms

Compliant mechanisms provide an attractive alternative to conventional rigid mechanisms in the design of ultra low-cost precision positioning systems. The desirable performance characteristics of these mechanisms including freedom from backlash, long life, light weight, and ease of fabrication/assembly make them an ideal solution to the problem of inexpensive precision positioning for microassembly. This paper presents a design for a 2 axis precision positioning system which makes use of large displacement compliant mechanisms, a room temperature and pressure molding fabrication process, commodity hardware, and a piecewise linear interpolation compensation scheme to achieve positioning performance suitable for automated assembly of sub-centimeter robotic and mechatronic devices

A Local Convergence Proof for the Minvar Algorithm for Computing Continuous Piecewise Linear Approximations

The class of continuous piecewise linear (PL) functions represents a useful family of approximants because invertibility can be readily imposed, and if a PL function is invertible, then it can be inverted in closed form. Many applications, arising, for example, in control systems and robotics, involve the simultaneous construction of a forward and inverse system model from data. Most approximation techniques require that separate forward and inverse models be trained, whereas an invertible continuous PL affords, simultaneously, the forward and inverse system model in a single representation. The minvar algorithm computes a continuous PL approximation to data. Local convergence of minvar is proven for the case when the data generating function is itself a PL function and available directly rather than through data.

Analysis of Shaft-Loaded Membrane Delamination Using Stationary Principles:

The following analysis investigates the delamination of an elastic membrane which on one side adheres to a smooth substrate while the other side is attached to a rigid cylindrical shaft. When the shaft is pulled perpendicularly from the substrate, this system is equivalent to the blister test of Malyshev and Salganik (International Journal of Fracture Mechanics, 1, 114 (1965)) and a solution is derived using the principle of minimum potential energy. Delamination can also be caused by rotating the shaft, which may be induced by a shear load and/or moment applied to the free end. For this more complicated system, an approximate solution is obtained from upper and lower bounds on strain energy that are derived from stationary principles with restricted deformation and stress fields, respectively. Beyond their applicability to blister tests, these results are relevant to the emerging study of biologically-inspired adhesives, as membranes constitute a critical attachment structure for a variety of wall-clinging organisms.

Invertible piecewise linear approximations for color reproduction

We consider the use of linear splines with variable knots for the approximation of unknown functions from data, motivated by control and estimation problems arising in color systems management. Unlike most popular nonlinear-in-parameters representations, piecewise linear (PL) functions can be simply inverted in a closed form. For the one-dimensional case, we present a study comparing PL and neural network (NN) approximations for several function families. Preliminary results suggest that PL, in addition to their analytical benefits, are at least competitive with NN in terms of sum square error, computational effort and training time.