In the absence of vision, grasping an object often relies on tactile feedback from the fingertips. As the finger pushes the object, the fingertip can feel the contact point move. If the object is known in advance, from this motion the finger may infer the location of the contact point on the object and thereby the object pose. This paper primarily investigates the problem of determining the pose (orientation and position) and motion (velocity and angular velocity) of a planar object with known geometry from such contact motion generated by pushing. A dynamic analysis of pushing yields a nonlinear system that relates through contact the object pose and motion to the finger motion. The contact motion on the fingertip thus encodes certain information about the object pose. Nonlinear observability theory is employed to show that such information is sufficient for the finger to “observe ” not only the pose but also the motion of the object. Therefore a sensing strategy can be realized as an observer of the nonlinear dynamical system. Two observers are subsequently introduced. The first observer, based on the result of [15], has its “gain ” determined by the solution of a Lyapunov-like equation; it can be activated at any time instant during a push. The second observer, based on Newton’s method, solves for the initial (motionless) object pose from three intermediate contact points during a push. Under the Coulomb friction model, the paper copes with support friction in the plane and/or contact friction between the finger and the object. Extensive simulations have been done to demonstrate the feasibility of the two observers. Preliminary experiments (with an Adept robot) have also been conducted. A contact sensor has been implemented using strain gauges. 1

This paper investigates how to "observe" a planar object being pushed by a finger. The pushing is governed by a nonlinear system that relates through contact the object pose and motion to the finger motion. Nonlinear observability theory is employed to show that the contact information is often sufficient for the finger to determine not only the pose but also the motion of the object. Therefore a sensing strategy can be realized as an observer of the nonlinear dynamical system, which is subsequently introduced. The observer, based on the result of [6], has its "gain" determined by the solution of a Lyapunov-like equation. Simulations have been done to demonstrate the feasibility of the observer. A sensor has been implemented using strain gauges and mounted on an Adept robot with which preliminary experiments have been conducted. From a general perspective, this work presents an approach for acquiring geometric and dynamical information about a task from a small amount of tactile data, ...

We present a general motion planning algorithm for robotic systems with a "stratified" configuration space. Such systems include quasi-static legged robots and kinematic models of object manipulation by finger repositioning. Our method is an extension of a nonlinear motion planning algorithm for smooth systems to the stratified case, where the relevant dynamics are not smooth. The method does not depend upon the number of legs or fingers; furthermore, it is not based on foot placement or finger placement concepts. Examples demonstrate the method.

We present a new method to reconstruct the shape of an unknown object using tactile sensors without requiring object immobilization. Instead, the robot manipulates the object without prehension. The robot infers the shape, motion and center of mass of the object based on the motion of the contact points as measured by tactile sensors. Our analysis is supported by simulation and experimental results.

This paper considers the problem of inferring local contact geometry from passive tactile information. The term "passive" means that the information results from motions of the object that are not necessarily under the control of the robot. To juxtapose, generally the term "active sensing" means that a robot actively explores an object, for instance with visual and/or tactile sensors that move around the object. This paper is not concerned with such active exploration. Instead, our goal is to determine how local shape geometry may be inferred from purely passive information. Shape recovery based on passive information will be useful both for dealing with unexpected events, as in the slippery grasping example above, and for more elaborate manipulation strategies, such as active exploration. 1.1 Motivation and Context

This papers analyzes the reliability of radius of curvature estimates from tactile sensor data. A linear elastic model is used to fit the indenter parameters, load, location, and curvature, to the sensor output. It was found that both contact models and calibration techniques could dramatically effect the bias and variance of the estimated indenter parameters. The Fourier series is found to be an appropriate basis in which to analyze both the calibration of tactile sensors and the problem of bandlimited shape interpretation. 1 Introduction Recently it has been shown that the human tactile sensory system is capable of fine shape discrimination from static touch [6]. Robotic tactile sensors have also been shown to have the capability of providing curvature information [5], however results using finiteelement models of tactile sensors indicate that reliable shape classification is hard [3]. It is well known that the rubber layer on the finger acts as a spatial low pass filter and that th...

Tactile Sensing and Control of a Planar Manipulator by Edward John Nicolson Doctor of Philosophy in Engineering - Electrical Engineering and Computer Sciences University of California at Berkeley Professor Ronald S. Fearing, Chair This dissertation explores the shape sensing capabilities of cylindrical tactile sensing fingers. Starting with an elastostatic model for the deformation of rubber fingers, sensor spacing and depth requirements are determined to allow reconstruction of subsurface strain fields with insignificant aliasing. Given this bandlimited version of the strain field, theoretical limits are found to classification and scaling of the perceived indentation. These theoretical results lead to the design of a silicone rubber tactile sensor which is characterized and calibrated to the model. The reliability of curvature estimates from the sensor is then determined. Finally, use of the sensor during manipulation is demonstrated. A spatial frequency domain model for the deformat...

This paper presents a general, nonholonomic dextrous manipulation and finger gaiting technique for robotic grasping problems. This method is general in that it is independent of the geometry of the grasped object and independent of the morphology of the mainipulating hand. This method is based upon a nonholonomic motion planning method for smooth system that has been extended to a certain class of discontinuous systems by recognizing a particular generic geometric structure underlying legged robotic locomotion and grasping problems, called a stratification The stratification is a decomposition of the configuration space of the system into subsets which correspond to the various combinations of fingers contacting the object. Additionally, associated with this manipulation methodology is a definition of manipulability that takes into account the fact that fingers may intermittently engage the object. Keywords: robotic grasping, finger gaiting, robotic manipulation, nonlinear control, mo...

We present a new method to reconstruct the shape of an unknown object using tactile sensors, without requiring object immobilization. Instead, sensing and nonprehensile manipulation occur simultaneously. The robot infers the shape, motion and center of mass of the object based on the motion of the contact points as measured by the tactile sensors. We present analytic results and simulation results assuming quasistatic dynamics. We prove that the shape and motion are observable in both the quasistatic and the fully dynamic case.

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