Face classification using touch with a humanoid robot hand

Sommer, Nicolas Le; Billard, Aude

doi:10.1109/humanoids.2012.6651508

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…However, the robustness and applicability of these strategies have only been evaluated on simple shaped objects (a cylinder and a sphere) in simulation. Other related works, such as our previous work [7], show that tactile exploration using an anthropomorphic robot hand can successfully recognize several human-like faces. In [8], a probabilistic approach is proposed to represent datapoints, which are collected from predefined grasps using a Schunk hand with tactile sensors at high frame rates.…”

Section: Introductionmentioning

confidence: 87%

Bimanual compliant tactile exploration for grasping unknown objects

Sommer

Billard

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Humans have an incredible capacity to learn properties of objects by pure tactile exploration with their two hands. With robots moving into human-centred environment, tactile exploration becomes more and more important as vision may be occluded easily by obstacles or fail because of different illumination conditions. In this paper, we present our first results on bimanual compliant tactile exploration, with the goal to identify objects and grasp them. An exploration strategy is proposed to guide the motion of the two arms and fingers along the object. From this tactile exploration, a point cloud is obtained for each object. As the point cloud is intrinsically noisy and un-uniformly distributed, a filter based on Gaussian Processes is proposed to smooth the data. This data is used at runtime for object identification. Experiments on an iCub humanoid robot have been conducted to validate our approach.

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Section: Introductionmentioning

confidence: 87%

Bimanual compliant tactile exploration for grasping unknown objects

Sommer

Billard

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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“…This added capability can also be beneficial in other applications, such as for use in robotic arms and humanoid robots. Tactile sensors play an important role in accomplishing various functions of humanoid robots, such as object manipulation (Yussof et al, 2007), robotic hands (Romano et al, 2011;Ataollahi et al, 2010;Schmitz et al, 2011), decoding and transferring tactile data collected in the fingerprint area of humanoid robots (Dahiya et al, 2009(Dahiya et al, , 2010 and classification of human facial features (Sommer and Billard, 2012). Also, communication between a robot and a human can be performed for different purposes, such as in the nursing context (Chen et al, 2014), socializing (Yohanan and MacLean, 2008) and affective touching (Yohanan and MacLean, 2008).…”

Section: Introductionmentioning

confidence: 99%

A new tactile array sensor for viscoelastic tissues with time-dependent behavior

et al. 2015

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Purpose – The purpose of this paper is to introduce a new tactile array sensor into the medical field to enhance current robotic minimally invasive surgery (RMIS) procedures that are still limited in scope and versatility. In this paper, a novel idea is proposed in which a tactile sensor array can measure rate of displacement in addition to force and displacement of any viscoelastic material during the course of a single touch. To verify this new array sensor, several experiments were conducted on a diversity of tissues from which it was concluded that this newly developed sensory offers definite and significant enhancements. Design/methodology/approach – The proposed array sensor is capable of extracting force, displacement and displacement rate in the course of a single touch on tissues. Several experiments have been conducted on different tissues and the array sensor to verify the concept and to verify the output of the sensor. Findings – It is shown that this new generation of sensors are required to distinguish the difference in hardness degrees of materials with viscoelastic behavior. Originality/value – In this paper, a new generation of tactile sensors is proposed that is capable of measuring indentation time in addition to force and displacement. This idea is completely unique and has not been submitted to any conference or journal.

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“…In our previous work [12], we tackled tactile exploration of human-like faces for classification, using fingertip tactile sensors and statistical encoding of the face models for robustness to proprioceptive noise. We also developed an algorithm for bi-manual haptic exploration of objects [13], using multiple phalanxes per finger, covered with tactile sensors, for the 3-d reconstruction of the objects' shapes.…”

Section: Tactile Explorationmentioning

confidence: 99%

Multi-contact haptic exploration and grasping with tactile sensors

Sommer

Billard

2016

Robotics and Autonomous Systems

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Haptic exploration has received a great deal of attention of late thanks to the variety of commercially available tactile sensors. While the majority of previous works consider control of a single contact point at a time, we tackle simultaneous control of multiple contact points on several links. In addition, we use information from the existing tactile signals to increase the number of points in contact. We demonstrate the usefulness of this form of control to speed up exploration, scanning and to compliantly grasp unknown objects. Our controller requires to know only the parts of the robot on which it is desirable to make contact and does not need a model of the environment besides the robot itself. We validate the algorithm in a set of experiments using a robotic hand covered with tactile sensors and arm. In a grasping application, the active adaptation of the fingers to the shape of the object ensures that the hand encloses the object with multiple contact points. We show that this improves the robustness of the grasp compared to simple enclosing strategies. When combined with an exploration strategy, our multi-contact approach offers an efficient use of tactile sensors on the whole surface of robotic fingers, and enables the robot to perform a rapid exploration of complex, non convex shapes while maintaining low contact forces. It is robust to variation in the approach angle and to changes in the geometry and orientation of the object.

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Face classification using touch with a humanoid robot hand

Cited by 5 publications

References 16 publications

Bimanual compliant tactile exploration for grasping unknown objects

Bimanual compliant tactile exploration for grasping unknown objects

A new tactile array sensor for viscoelastic tissues with time-dependent behavior

Multi-contact haptic exploration and grasping with tactile sensors

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