location of a contact, the force at the interface and the moment about the contact normals. Called "intrinsic" contact sensing for the use of in- ternal force and torque measurements, this method allows for practical devices which provide simple, relevant contact information in practical robotic applications. Such sensors have been used in conjunction with robot hands to identify objects, determine surface friction, detect slip, augment grasp stability, measure object mass, probe surfaces, control collision and a variety of other useful tasks. This paper describes the theoretical basis for their operation and provides a framework for future device design.

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, ...

This paper employs proprioceptive information (joint angles and torques) to estimate properties of the contact between a planar robot and an unknown object without specifically requiring strategic manipulator motions. The algorithm presented tackles this task in two stages; a contact localization analysis is followed by a force domain contact detection analysis. In the former, the Cartesian endpoint velocities are used for each link to obtain an estimate of the location of a hypothetical contact point on the link surface. A second observer, based on the displacement between two consecutive postures of the manipulator, provides an estimate of the error associated with this location. This data is fused over time by tracking the contact location using a linear observer and results in a hypothetical contact location, an associated uncertainty region, and a surface normal estimate. The detection phase uses torque domain evidence and the location estimates to verify the existence of each of ...

Inspired by nature's e#ective use of tactile feedback for rapid maneuvering, we designed a passive, highly compliant tactile sensor for Sprawlette, a hexapedal running robot. To bridge the gap between biology and design, we took initial steps toward understanding how the cockroach, Periplaneta americana, uses antenna feedback to control its orientation during a rapid wall following behavior. First, we developed a simple template model for antenna-based wall following. Second, we collected initial cockroach data that supports the idea that the rate of convergence to the wall or "tactile flow" is being used, in part, for controlling body orientation. Based on these steps, we designed and calibrated a prototype tactile sensor to measure Sprawlette's angle and distance relative to a straight wall, and employed a simple bio-inspired control law that can stabilize the template dynamics. Finally, we integrated the sensor and controller on Sprawlette and showed empirically that stabilizing Sprawlette during wall following does indeed require tactile flow, as predicted.

Grasping a curved object free in the plane may be done through rolling a pair of fingers on the object’s boundary. Each finger is equipped with a tactile sensor able to record any instantaneous point contact with the object. Contact kinematics reveal a relationship between the amount of finger rotations and the total curvatures of the boundary segments of the fingers and the object respectively traversed by the two contact points during the same period of rolling. Such relationship makes it possible to localize both fingers relative to the object from a few pairs of simultaneously taken finger contacts at different time instants. A least squares formulation of this localization problem can then be solved by the Levenberg-Marquardt algorithm. Simulation results are presented. After localization, a simple open loop strategy is used to control the continual rolling of the fingers until they simultaneously reach two locations on the object’s boundary where a grasp is finally performed.

The limitations of rigid #ngertips in the precise and algorithmic study of manipulation have been discussedin many works, some dating back more than a decade. Despite that fact, much of the work in dexterous manipulation has continued to use the #point-contact" model for #nger-object interactions. In fact, most of the existing tactile sensing technologies are not adaptable to deformable #ngertips. In this work we report on experimental results obtained with a deformable tactile sensor whose properties are well-suited to manipulation. The results presented here show that the sensor described provides a rich set of tactile data. 1 Introduction In this work we describe a deformable image-based tactile sensor whose output is an approximation of the tactile surface itself. We present a set of basic tactile sensing experiments designed to demonstrate aspects of the sensor's performance. The ability of our sensor to deform while accurately localizing contact#s# makes it a promising tool fo...

Abstract—This paper describes a tactile sensing system based on a force/torque sensor for the feet of a pipe crawling robot. Such a sensing system is needed for better optimization of force and joint load distribution and a safer avoidance of the risk of foot slippage. While conventional tactile sensing devices typically provide information concerning the spatial distribution of normal pressures, the intrinsic contact sensing system presented in this text only measures the three components of the contact force and two components of the resultant torque. These five parameters are shown to be sufficient to estimate the location of the contact point and hence the orientation of the local contact surface. Such information can then be used by the crawler’s control system for the real-time computation of an optimized foot force distribution. The intrinsic tactile sensing method has been experimentally tested on a single leg test setup, while the optimization of force distribution is already functioning in the TUM Pipe Crawling Robot (only with a different, more unripe, sensing system for the contact orientations). Index Terms—Force control, legged locomotion, robot sensing systems, service robots, tactile sensors. I.

force/torque) sensors, as considered within the framework of optimal design theory. Optimal design procedures consist of finding the combination of design variables that extremizes some optimality criterion: provided a suitable mathematical formulation of the problem, solutions can be efficiently obtained through currently avMlable numerical tech- niques. The principal goal of this paper is to identify a mathematical objective function, whose minimization corresponds to the optimiza- tion of sensor accuracy. The methodology employed is derived from linear algebra and analysis of numerical stability. An objective func- tion which can be applied to a large class of sensor configurations is proposed. The problem of optimizing the number of basic transducers employed in a multi-component sensor is also addressed. Finally, applications of the proposed method to the design of a simple sensor as well as to the optimization of a novel, 6-axis miniaturized sensor are discussed.

Programming by human demonstration is a new paradigm for the development of robotic applications that focuses on the needs of task experts rather than programming experts. The traditional text-based programming paradigm demands the user be an expert in a particular programming language and further demands that the user can translate the task into this foreign language. This level of programming expertise generally precludes the user from having detailed task expertise because his/her time is devoted to the practice of programming, not the practice of the task. The goal of programming by demonstration is to eliminate both the programming language expertise and, more importantly, the expertise required to translate the task into the language. Gesture-Based Programming is a new form of programming by human demonstration that views the demonstration as a series of inexact "gestures" that convey the "intention " of the task strategy, not the details of the strategy itself. This is analogous...