Development of Robotic End-Effector Using Sensors for Part Recognition and Grasping

Biswal, Bibhuti Bhusan; Sahu, OP; Mukharji, S; Jha, Panchanand

doi:10.12720/ijmse.3.1.39-43

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Recent advances in mechanical design and control allowed robotic systems to make soft contact with the environment (Biswal et al , 2015; Jha and Biswal, 2014). The traditional motion classification methods usually use the hand-centered view (Leidner et al , 2015) and classify according to finger position, relative motion (Bullock et al , 2012) or geometric size.…”

Section: Related Workmentioning

confidence: 99%

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

Cong

Liu

et al. 2023

RIA

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Purpose Robots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes. Design/methodology/approach This paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory. Findings To verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment. Originality/value The robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.

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Section: Related Workmentioning

confidence: 99%

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

Cong

Liu

et al. 2023

RIA

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“…However, such methods deals with parameterization of the geometry of the objects and cannot be applied for grasping. Biswal et al [11] developed a multiple sensor integrated robot end-effector which can be gainfully used for finding the best grasp for a set of objects. This is done by using a predefined parameterization of the object surface and the hand poses, a method which inspired this work.…”

Section: Related Work and Reviewmentioning

confidence: 99%

An Integrated Approach of Sensors to Detect Grasping Point for Unstructured 3-D Parts

Sahu¹

2017

IJET

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Grasping of unstructured parts is a problem in automated assembly. In this paper, grasping of unstructured manufacturing parts is considered, where the parts are unambiguously seen first time via vision sensor. The problem lies on grasping these unknown parts, where the three dimensional view of parts is not available. For grasping efficiently, the end-effector is equipped with a vision and ultrasonic sensor. The demonstration is explained in details in the paper. The desired grasping point is found out by the bounding rectangle and image frame size contour to calculate the total number of the pixel on parts. Acceptable parts grasping point can be calculated in the presence of HSV noise. Experiments analysis is done on different unknown objects for evaluation.

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“…Better result was found by applying the proposed method than the other existing edge detection methods like Canny's, Sobel. A robotic end-effector integrated with multiple sensors was developed by O. P. Sahu et al [11] for the identification of unstructured parts and anonymous environment in industrial robot. They have investigated the state-of-art of the sensor technology for automated assembly.…”

Section: Related Workmentioning

confidence: 99%

Feature Based Face Detection in HRI

Balabantaray¹,

Sahu²,

Biswal³

2016

JOIG

Self Cite

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Human being is becoming closer and more interested in the collaboration with robots in their daily life. For a better integration with robots, Face detection is a very essential aspect of HRI. In this work, a method for face detection using LabVIEW is proposed. ELM technique is used to filter real face images along with the corner filter. The work is focused on detection of face based on analysis of feature extracted.

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Development of Robotic End-Effector Using Sensors for Part Recognition and Grasping

Cited by 5 publications

References 7 publications

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

An Integrated Approach of Sensors to Detect Grasping Point for Unstructured 3-D Parts

Feature Based Face Detection in HRI

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