Quadrupedal Bounding with an Actuated Spinal Joint

Most legged vertebrates use flexible spines and supporting muscles to provide auxiliary power and dexterity for dynamic behaviors, resulting in higher speeds and additional maneuverability during locomotion. However, most existing legged robots capable of dynamic locomotion incorporate only a single rigid trunk with actuation limited to legs and associated joints. In this paper, we investigate how quadrupedal bounding can be achieved in the presence of an actuated spinal joint and characterize associated performance improvements compared to bounding with a rigid robot body. In the context of both a new controller structure for bounding with a body joint and existing bounding controllers for the rigid trunk, we use optimization methods to identify the highest performance gait parameters and establish that the spinal joint allows increased forward speeds and hopping heights

SVAS3: Strain Vector Aided Sensorization of Soft Structures

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations.ISSN:1424-822

Statistical reprogramming of macroscopic self-assembly with dynamic boundaries

Self-assembly is a ubiquitous process that can generate complex and functional structures via local interactions among a large set of simpler components. The ability to program the self-assembly pathway of component sets elucidates fundamental physics and enables alternative competitive fabrication technologies. Reprogrammability offers further opportunities for tuning structural and material properties but requires reversible selection from multistable self-assembling patterns, which remains a challenge. Here, we show statistical reprogramming of two-dimensional (2D), noncompact self-assembled structures by the dynamic confinement of orbitally shaken and magnetically repulsive millimeter-scale particles. Under a constant shaking regime, we control the rate of radius change of an assembly arena via moving hard boundaries and select among a finite set of self-assembled patterns repeatably and reversibly. By temporarily trapping particles in topologically identified stable states, we also demonstrate 2D reprogrammable stiffness and three-dimensional (3D) magnetic clutching of the self-assembled structures. Our reprogrammable system has prospective implications for the design of granular materials in a multitude of physical scales where out-of-equilibrium self-assembly can be realized with different numbers or types of particles. Our dynamic boundary regulation may also enable robust bottom-up control strategies for novel robotic assembly applications by designing more complex spatiotemporal interactions using mobile robots.Electronic Components, Technology and Material

A Localization Method for Untethered Small-Scale Robots using Electrical Impedance Tomography

International audienceUntethered small-scale robots can be potentially used in medical applications such as minimally invasive surgeries and targeted drug delivery. This paper introduces a new localization method using Electrical Impedance Tomography (EIT), which is an emerging medical imaging technique, to dynamically track small-scale robots. The proposed approach provides the electrical conductivity distribution within the robot workspace from a set of electrical stimulations and voltage measurements gathered from eight electrodes placed at its boundary. The position of the robot can be deduced from the conductivity map that is reconstructed with the contrast in electrical properties between the robot and the background medium. This method is experimentally validated by successfully tracking the 2D motion of 4 different magnetically actuated robots within a cylindrical arena (30 mm in diameter and 4.2 mm high). The smallest detected robot is 1.5 × 1.5 × 1 mm3 . The proposed tracking method provides a non-invasive technology with low-cost and high-speed potential that would be significant and useful for the position feedback control of untethered devices for biomedical applications in the future.&nbsp

Active Sensing System with In Situ Adjustable Sensor Morphology

<div><p>Background</p><p>Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements.</p> <p>Methodology</p><p>This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. </p> <p>Conclusions/Significance</p><p>The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed. </p> </div

Different physical interactions and sensing characteristics enabled by adjusting the sensor morphology, and purposive motion, in situ.

<p>(a) model of the physical interaction for discriminating the softness of the target object (b) corresponding sensing characteristics, i.e. range and sensitivity (c) model of the physical interaction for discriminating the temperature of the object (d) the corresponding sensing characteristics (note: the standard deviation for temperature sensing range is divided by two for the sake of clarity).</p

Hardware and software implementation of the proposed concept.

<p>(a) Complete workspace of the experiment which includes a robot manipulator equipped with HMA handling units on its end effector (b) The robot’s end effector which is composed of a solid HMA block which is fed to HMA supplier. Fabricated HMA units can be connected to HMA connector. A camera is mounted to perform visual processing tasks during sensing. (c) Software implementation of the proposed approach which is composed of two main parts: the in-situ adjustment of the sensor morphology, and the active sensing via motion (d) Flowchart showing the visual processing algorithm used for softness and temperature case studies. </p