Real-time pose estimation of an object manipulated by multi-fingered hand using 3D stereo vision and tactile sensing

Honda, Kyuhei; Hasegawa, Tsutomu; Kiriki, Toshihiro; Matsuoka, Toshifumi

doi:10.1109/iros.1998.724860

Cited by 28 publications

(7 citation statements)

References 5 publications

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“…Estimation of an object's pose combining stereo vision and a force-torque sensor mounted on the wrist of a robot was reported by Hebert et al [7], who also used the joint position to estimate the location of the fingers with respect to the object's faces. Honda et al [8] used a combination of tactile and vision sensing to estimate an object's pose, assuming that the object is composed of plain and quadratic surfaces. This paper extends the authors' previous work in [9], where only the distance between fingers and object was considered 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) November 3-7, 2013.…”

Section: Introductionmentioning

confidence: 99%

Combining touch and vision for the estimation of an object's pose during manipulation

Bimbo

Seneviratne

Althoefer

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Robot grasping and manipulation relies mainly on two types of sensory data: vision and tactile sensing. Localisation and recognition of the object is typically done through vision alone, while tactile sensors are commonly used for grasp control. Vision performs reliably in uncluttered environments, but its performance may deteriorate when the object is occluded, which is often the case during a manipulation task, when the object is in-hand and the robot fingers stand between the camera and the object.This paper presents a method to use the robot's sense of touch to refine the knowledge of a manipulated object's pose from an initial estimate provided by vision. The objective is to find a transformation on the object's location that is coherent with the current proprioceptive and tactile sensory data. The method was tested with different object geometries and proposes applications where this method can be used to improve the overall performance of a robotic system. Experimental results show an improvement of around 70% on the estimate of the object's location when compared to using only vision.

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Section: Introductionmentioning

confidence: 99%

Combining touch and vision for the estimation of an object's pose during manipulation

Bimbo

Seneviratne

Althoefer

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…Based on the assumption that visually similar surfaces are likely to have similar haptic properties, vision is used to create dense haptic maps efficiently across visible surfaces with sparse haptic labels in [168]. Vision can also provide an approximate initial estimate of the object pose that is then refined by tactile sensing using local [173], [174] or global optimization [170].…”

Section: Contact Pointsmentioning

confidence: 99%

Robotic tactile perception of object properties: A review

et al. 2017

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Abstract-Touch sensing can help robots understand their surrounding environment, and in particular the objects they interact with. To this end, roboticists have, in the last few decades, developed several tactile sensing solutions, extensively reported in the literature. Research into interpreting the conveyed tactile information has also started to attract increasing attention in recent years. However, a comprehensive study on this topic is yet to be reported. In an effort to collect and summarize the major scientific achievements in the area, this survey extensively reviews current trends in robot tactile perception of object properties. Available tactile sensing technologies are briefly presented before an extensive review on tactile recognition of object properties. The object properties that are targeted by this review are shape, surface material and object pose. The role of touch sensing in combination with other sensing sources is also discussed. In this review, open issues are identified and future directions for applying tactile sensing in different tasks are suggested.

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“…Visuo-tactile methods have attained attributes such as elasticity, mass and relational constraints [10] and object pose [11], [12]. Shape has been determined with methods such as tactile glances at discrete points on the object [13], visual and tactile feedback from grasping [14], combining visual and tactile exploratory procedures [15] and visuo-tactile fusion [16].…”

Section: Background and Related Workmentioning

confidence: 99%