Heinz Woern

A tactile proximity sensor

This paper introduces a novel tactile sensor with the ability to detect objects in the sensors near proximity. For both tasks, the same capacitive sensing principle is used. The tactile part of the sensor provides a tactile sensor array enabling the sensor to gather pressure profiles of the mechanical contact area. Several tactile sensors have been developed in the past. These sensors lack the capability of detecting objects in their near proximity before a mechanical contact occurs. Therefore, we developed a tactile proximity sensor, which is able to measure the current flowing out of or even into the sensor. Measuring these currents and the exciting voltage makes a calculation of the capacitance coupled to the sensors surface and, using more sensors of this type, the change of capacitance between the sensors possible. The sensors mechanical design, the analog/digital signal processing and the hardware efficient demodulator structure, implemented on a FPGA, will be discussed in detail.

Tactile sensor and algorithm to detect slip in robot grasping processes

In this paper we introduce a tactile slip sensor for an anthropomorphic robot hand, the measurement circuit and the corresponding algorithm to determine slip states. The main slip sensor components consist of a silicone rubber surface which covers a PVDF sensor. After the amplification of the signal it is processed by a discrete short-time Fourier transform. The resulting spectrogram is processed by a principal component analysis to determine the main signal components. For a classification of three states (‘slip’, ‘signal but no slip’ and ‘noise’) a k-nearest neighbour classifier has been trained with the main signal components and serves for discrimination of slip states on the sensors surface. The build-up of the sensor and the experimental setup will be briefly explained, the signal processing and the results will be discussed in detail.

Tactile sensor on a magnetic basis using novel 3D Hall sensor - First prototypes and results

In this paper, a new operating principle for a tactile sensor for medical diagnostics is proposed based on the measurement of three-dimensional magnetic fields. A permanent magnet and the newly developed 3D-Hall sensor AS54xx of the Fraunhofer Institute for Integrated Circuits (IIS) in Erlangen, Germany, are embedded in one silicone pad. An external force changes the position of the magnet in relation to the AS54xx, thus changing the measured magnetic field in three dimensions. In contrast to conventional tactile sensors, one sensor cell provides three dimensional information about external forces, thus making it potentially possible to detect tumors by palpation with only this one sensor cell. Three prototypes of the tactile sensor with different silicones and permanent magnets have been fabricated, and the feasibility of the operating principle has been proven for axial forces with laboratory experiments. Hysteresis effects of the tactile sensor have turned out to be negligible.

A distributed control architecture for autonomous mobile robots - implementation of the Karlsruhe Multi-Agent Robot Architecture (KAMARA)

The main advantage of distributed controlled robots and subsystems is the decentralized task execution by the system components. In this way, properties for the design of flexible control architectures like modularity, fault-tolerance, integrability and extendibility are easily obtained; furthermore, it is possible to use the concepts of distributed knowledge and decentralized world representation. On the other hand, coordination between the components, e.g. path planning for collision avoidance between both manipulators in a two-arm system, is very difficult to guarantee. To explain these concepts, the Karlsruhe Autonomous Mobile Robot (KAMRO), which is being developed at our institute, is considered. The robot system consists of several subcomponents like two manipulators, hand-eye cameras, one overhead camera and a mobile platform. Extensions to the distributed control architecture KAMARA (KArlsruhe Multi-Agent Robot Architecture) are described that are used to overcome coordination problems, e.g. as c...

Teleoperated assembly of a micro‐lens system by means of a micro‐manipulation workstation

Purpose – The aim of the research is to perform an accurate micromanipulation task, the assembly of a lens system, implementing safe procedures in a flexible microrobot‐based workstation for micromanipulation.Design/methodology/approach – The approach to the micromanipulation research issue consists in designing and building a micromanipulation station based on mobile microrobots, with 5 degrees of freedom and a size of a few cm3, capable of moving and manipulating by the use of tube‐shaped and multilayered piezo‐actuators. Controlled by visual and force/tactile sensor information, the micro‐robot is able to perform manipulation with a motion resolution down to 10 nm in a telemanipulated or semi‐automated mode, thus freeing human operators from the difficult task of handling minuscule objects directly. Equipped with purposely‐developed grippers, the robot can take over high‐precise grasping, transport, manipulation and positioning of mechanical or biological micro‐objects. A computer system using PC‐compa...

Design and control of flexible microrobots for an automated microassembly desktop station

There is an increasing interest in performing microsystem assembly using flexible microrobots. A new concept of a flexible robot-based micro-assembly desktop station and tow prototypes of piezoelectric microassembly robots, MINIMAN and PROHAM, were already presented at the last years SPIE meeting. In this paper, the motion control approach of these robots is discussed. This control approach is based on the geometric description of the robot platform and aims at following the optimal motion trajectory to minimize the operation time and to keep the robot end effector under microscope supervision. Besides excellent abilities both robots have some disadvantages such as the relatively high drive voltage of the piezoactuators or the instability of grasp-and-hold operations. For this reason, several new piezoelectric microrobots that employ different locomotion and object handling principle have lately been developed. The design and functions of these microrobots are shown.

Sensor-aided Milling with a Surgical Robot System

In this paper sources of errors are pointed out that occur using a robot system in order to cut bones. It is shown that the deflection of the robot tool must not be neglected if an accuracy in the range of one millimeter (from planning to execution) is required, since the tool deflection is up to 1.5 millimeters depending on the affecting torques. Therefore, special focus is set on methods which cope with this problem. A calibration approach considering the deflection of the robot tool is presented. After this calibration, it is possible to consider the tool deflection during the registration procedure (ball-in-cone strategy) as well as during the intervention. Furthermore, a discrete feed control algorithm is outlined.

Simulation tool for 3D shape sensors based on Fiber Bragg gratings and optimization of measurement points

3D shape sensing using Fiber Bragg gratings has attracted the interest of several research groups in recent years, but so far no possibility has been presented to optimize the sensing system by simulation. Almost always, the gratings (the points of strain measurement) are distributed equidistantly, and the reconstruction algorithm has not been verified by simulation. In this paper we present our simulation tool that works on a mathematical basis and includes two parts: the first part describes how to determine the strains of Fiber Bragg gratings mounted along a given shape. The second part describes our algorithm to reconstruct the shape from this strain data using theory of differential geometry. This reconstruction algorithm is evaluated within the simulation environment and can be adapted to different system behaviors like circular bending of the instrument, cubic bending or bending according to the Euler beam theory. Furthermore, the gratings can be optimized with respect to their position and designated Bragg wavelength. To demonstrate the effectiveness of the simulation tool, an optimization has been conducted for the grating positions along a shape with two independent bendable segments. For each configuration of the shape, the reconstruction results using the optimized grating positions were significantly better than when using equidistantly distributed gratings.

Combining shape sensor and haptic sensors for highly flexible single port system using Fiber Bragg sensor technology

Single port surgery is a promising approach to further optimize the benefits of robot assisted minimally invasive surgery. Advantages include further minimization of trauma and reduction of scars, but it also increases the need for flexible, high-end instruments and miniaturized sensors. This paper describes a new concept of a miniaturized sensor system which combines a kinesthetic sensor, a tactile sensor and a position sensor. Latter is realized as a shape sensor. The combination of the sensors is possible because they are all based on Fiber Bragg Grating technology. A concept for each sensor is also presented. They are improved compared to current research and adapted to our needs. The miniaturized sensor system is integrated into an innovative, highly flexible single port system.

Pixelwise object class segmentation based on synthetic data using an optimized training strategy

In this paper we present an approach for low-level body part segmentation based on RGB-D data. The RGB-D sensor is thereby placed at the ceiling and observes a shared workspace for human-robot collaboration in the industrial domain. The pixelwise information about certain body parts of the human worker is used by a cognitive system for the optimization of interaction and collaboration processes. In this context, for rational decision making and planning, the pixelwise predictions must be reliable despite the high variability of the appearance of the human worker. In our approach we treat the problem as a pixelwise classification task, where we train a random decision forest classifier on the information contained in depth frames produced by a synthetic representation of the human body and the ceiling sensor, in a virtual environment. As shown in similar approaches, the samples used for training need to cover a broad spectrum of the geometrical characteristics of the human, and possible transformations of the body in the scene. In order to reduce the number of training samples and the complexity of the classifier training, we therefore apply an elaborated and coupled strategy for randomized training data sampling and feature extraction. This allows us to reduce the training set size and training time, by decreasing the dimensionality of the sampling parameter space. In order to keep the creation of synthetic training samples and real-world ground truth data simple, we use a highly reduced virtual representation of the human body, in combination with KINECT skeleton tracking data from a calibrated multi-sensor setup. The optimized training and simplified sample creation allows us to deploy standard hardware for the realization of the presented approach, while yielding a reliable segmentation in real-time, and high performance scores in the evaluation.