Localizing a polyhedral object in a robot hand by integrating visual and tactile data

Boshra, M.; Zhang, Hong

doi:10.1016/s0031-3203(99)00059-x

Cited by 7 publications

(3 citation statements)

References 24 publications

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“…Nevertheless, we are assuming that the vision modality is available at first so that the uncertainty can be efficiently narrowed down at the start. In general, the vision modality makes it possible to detect features globally, whereas tactile sensing typically has only a local scope (see [10] for a comparison of visual and tactile data). Therefore, it is usually better to use the vision modality at first (if available), because a wider field can be observed.…”

Section: Discussionmentioning

confidence: 99%

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

Nottensteiner

Sachtler

Albu‐Schäffer

2021

J Intell Robot Syst

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Robotic assembly tasks are typically implemented in static settings in which parts are kept at fixed locations by making use of part holders. Very few works deal with the problem of moving parts in industrial assembly applications. However, having autonomous robots that are able to execute assembly tasks in dynamic environments could lead to more flexible facilities with reduced implementation efforts for individual products. In this paper, we present a general approach towards autonomous robotic assembly that combines visual and intrinsic tactile sensing to continuously track parts within a single Bayesian framework. Based on this, it is possible to implement object-centric assembly skills that are guided by the estimated poses of the parts, including cases where occlusions block the vision system. In particular, we investigate the application of this approach for peg-in-hole assembly. A tilt-and-align strategy is implemented using a Cartesian impedance controller, and combined with an adaptive path executor. Experimental results with multiple part combinations are provided and analyzed in detail.

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Section: Discussionmentioning

confidence: 99%

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

Nottensteiner

Sachtler

Albu‐Schäffer

2021

J Intell Robot Syst

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“…Son et al 47 reported the experimental result about using both visual and tactile information for manipulator grasping and pointed out that with the introduction of tactile information, more precise result can be obtained. Boshra and Zhang 48 realized localization of polyhedron by integrating visual and tactile information.…”

Section: Visual-tactile Fusion For Object Recognitionmentioning

confidence: 99%

Recent progress on tactile object recognition

Liu

Sun

et al. 2017

International Journal of Advanced Robotic Systems

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Conventional visual perception technology is subject to many restrictions, such as illumination, background clutter, and occlusion. Many intrinsic properties of objects, like stiffness, hardness, and internal state, cannot be effectively perceived by visual sensors. For robots, tactile perception is a key approach to obtain environmental and object information. Different from vision sensors, tactile sensors can directly measure some physical properties of objects and environment. At the same time, humans also utilize touch sensory receptors as an important means to perceive and interact with the environment. In this article, we present a detailed discussion on tactile object recognition problem. We divide the current studies on the tactile object recognition into three subcategories and detailed analysis has been put forward on them. In addition, we also discuss some advanced topics such as visual-tactile fusion, exploratory procedure, and data sets.

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“…Significant amount of work has already been done by researcher to develop robot control strategies that would maximise the capability of individual sensing technologies through their strategic integration. (Namiki and Ishikawa, 1996), (Allen et al, 1999), (Boshra and Zhang, 2000), and (Prats et al, 2009) used sensor fusion strategies to integrate vision and tactile sensing to improve grasping. Pelossof et al (2004) used simulation based on SVM (Support Vector Machine) method to find optimum grasps for complex shape objects.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling of a Grasping and Manipulation Controller

Dzitac

Mazid

2012

Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics

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This paper presents the development of a robot grasping and manipulation control system, including the modelling approach for the control functions, and the criteria used for functional module design in order to achieve the required functionality and allow its integration into the overall control model. This work is an example of a practical implementation of a robotic grasping and manipulation controller and may be relevant to researchers looking for an example of a practical controller design "from scratch".

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Localizing a polyhedral object in a robot hand by integrating visual and tactile data

Cited by 7 publications

References 24 publications

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

Towards Autonomous Robotic Assembly: Using Combined Visual and Tactile Sensing for Adaptive Task Execution

Recent progress on tactile object recognition

Modelling of a Grasping and Manipulation Controller

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