Tactile Sensors for Force Control and Contact Recognition

2011 15th International Conference on Advanced Robotics (ICAR), 2011

In this paper, we present a novel tactile-array sensor for use in robotic grippers based on flexible piezoresistive rubber. We start by describing the physical principles of piezoresistive materials, and continue by outlining how to build a flexible tactile-sensor array using conductive thread electrodes. A real-time acquisition system scans the data from the array which is then further processed. We validate the properties of the sensor in an application that classifies a number of household objects while performing a palpation procedure with a robotic gripper. Based on the haptic feedback, we classify various rigid and deformable objects. We represent the array of tactile information as a time series of features and use this as the input for a k-nearest neighbors classifier. Dynamic time warping is used to calculate the distances between different time series. The results from our novel tactile sensor are compared to results obtained from an experimental setup using a Weiss Robotics tactile sensor with similar characteristics. We conclude by exemplifying how the results of the classification can be used in different robotic applications.

Soft Science, 2023

The robotic with integrated tactile sensors can accurately perceive contact force, pressure, vibration, temperature and other tactile stimuli. Flexible tactile sensing technologies have been widely utilized in intelligent robotics for stable grasping, dexterous manipulation, object recognition and human-machine interaction. This review presents promising flexible tactile sensing technologies and their potential applications in robotics. The significance of robotic sensing and tactile sensing performance requirements are first described. The commonly used six types of sensing mechanisms of tactile sensors are briefly illustrated, followed by the progress of novel structural design and performance characteristics of several promising tactile sensors, such as highly sensitive pressure and tri-axis force sensor, flexible distributed sensor array, and multi-modal tactile sensor. Then, the applications of using tactile sensors in robotics such as object properties recognition, grasping and manipulation, and human-machine interactions are thoroughly discussed. Finally, the challenges and future prospects of robotic tactile sensing technologies are discussed. In summary, this review will be conducive to the novel design of flexible tactile sensors and is a heuristic for developing the next generation of intelligent robotics with advanced tactile sensing functions in the future.

Robotics and Autonomous Systems, 2015

Tactile sensing is an essential element of autonomous dexterous robot hand manipulation. It provides information about forces of interaction and surface properties at points of contact between the robot fingers and the objects. Recent advancements in robot tactile sensing led to development of many computational techniques that exploit this important sensory channel. This paper reviews current state-of-the-art of manipulation and grasping applications that involve artificial sense of touch and discusses pros and cons of each technique. The main issues of artificial tactile sensing are addressed. General requirements of a tactile sensor are briefly discussed and the main transduction technologies are analyzed. Twenty eight various tactile sensors, each integrated into a robot hand, are classified in accordance with their transduction types and applications. Previously issued reviews are focused on hardware part of tactile sensors, whereas we present an overview of algorithms and tactile feedback-based control systems that exploit signals from the sensors. The applications of these algorithms include grasp stability estimation, tactile object recognition, tactile servoing and force control. Drawing from advancements in tactile sensing technology and taking into consideration its drawbacks, this paper outlines possible new directions of research in dexterous manipulation.

Both tactile and visual sensing are important to solve problems of uncertainties inherent to the grasping tasks. In this paper, a hybrid approach based on combining tactile and RGBD data is proposed for control the robotic manipulation of elastic objects. The proposed method detects both interaction and lack of contact among fingertips and object. Also, this approach measures deformations to determine appropriated finger movements when the object's geometry changes in real time as a result of the deformation caused by the pressure. This approach was evaluated on a multi-fingered robot hand with tactile sensors in real experiments.

Sensors (Basel, Switzerland), 2018

This work presents a novel and simple approach in the area of manipulation of unknown objects considering both geometric and mechanical constraints of the robotic hand. Starting with an initial blind grasp, our method improves the grasp quality through manipulation considering the three common goals of the manipulation process: improving the hand configuration, the grasp quality and the object positioning, and, at the same time, prevents the object from falling. Tactile feedback is used to obtain local information of the contacts between the fingertips and the object, and no additional exteroceptive feedback sources are considered in the approach. The main novelty of this work lies in the fact that the grasp optimization is performed on-line as a reactive procedure using the tactile and kinematic information obtained during the manipulation. Experimental results are shown to illustrate the efficiency of the approach.

IEEE International Conference on Robotics and Automation (ICRA), 2014

The majority of the works on grasping consider both object as well as robot hand parameters to be accurately known and do not take into account the constraints imposed by the robot hand. In this paper, a complete methodology is proposed that handles the grasping problem under a wide range of uncertainties. Initially, we search for an acceptable posture that provides robustness against positioning inaccuracies and maximizes the ability of the robot hand to exert forces on the object. Subsequently, in order to secure the grasp stability, we also deal with the determination of sufficient contact forces. Finally, an appropriate tactile sensor setup, mounted on the robot hand, allow us to reduce the magnitude of uncertainty regarding the grasping parameters. The efficiency of our approach is validated through extensive experimental paradigms using a 15 DoF DLR/HIT II robotic hand attached at the end effector of a 7 DoF Mitsubishi PA10 robotic manipulator.

Sensors and Actuators A: Physical, 2011

As the field of robotics is expanding from the fixed environment of a production line to complex human environments, robots are required to perform increasingly human-like manipulation tasks, moving the state-of-the-art in robotics from grasping to advanced in-hand manipulation tasks such as regrasping, rotation and translation. To achieve advanced in-hand manipulation tasks, robotic hands are required to be equipped with distributed tactile sensing that can continuously provide information about the magnitude and direction of forces at all contact points between them and the objects they are interacting with. This paper reviews the state-of-the-art in force and tactile sensing technologies that can be suitable within the specific context of dexterous in-hand manipulation. In previous reviews of tactile sensing for robotic manipulation, the specific functional and technical requirements of dexterous in-hand manipulation, as compared to grasping, are in general not taken into account. This paper provides a review of models describing human hand activity and movements, and a set of functional and technical specifications for in-hand manipulation is defined. The paper proceeds to review the current state-of-the-art tactile sensor solutions that fulfil or can fulfil these criteria. An analytical comparison of the reviewed solutions is presented, and the advantages and disadvantages of different sensing technologies are compared.

Robotics and Automation (ICRA), …, 2010

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this work, we present a tactile perception strategy that allows any mobile robot with tactile sensors in its gripper to measure a set of generic tactile features while grasping an object. We propose a hybrid velocity-force controller, that grasps an object safely and reveals at the same time its deformation properties. As an application, we show that a robot can use these features to distinguish the open/closed and fill state of bottles and cans -purely from tactile sensing -from a small training set. To prove that this is a hard recognition problem, we also conducted a comperative study with 24 human test subjects. We found that the recognition rate of the human subjects were comparable to our robotic gripper.

2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2020

Simulated worlds are important enablers and accelerators of new algorithms for autonomous robot applications. A framework for tactile servoing in the simulated world is presented. This framework includes a general model of tactile sensing arrays that can simulate the behavior of a real tactile sensing array thanks to an empirical characterization procedure. After obtaining the precise sensor model, different tactile servoing schemes can be implemented in the framework by controlling contact features, including points and lines extracted from the simulated contact images. Several experiments have been performed in order to guarantee the correspondence between the simulated results generated by the framework and the real ones executed with different sensors and robots.