Abstract
This paper aims to develop grasping and manipulation capability along with autonomous navigation and localization in a wheelchair-mounted robotic arm to serve patients. Since the human daily environment is dynamically varied, it is not possible to enable the robot to know all the objects that would be grasped. We present an approach to enable the robot to detect, grasp and manipulate unknown objects. We propose an approach to construct the local reference frame that can estimate the object pose for detecting the grasp pose of an object. The main objective of this paper is to present the grasping and manipulation approach along with a navigating and localization method that can be performed in the human daily environment. A grid map and a match algorithm is used to enable the wheelchair to localize itself using a low-power computer. The experimental results show that the robot can manipulate multiple objects and can localize itself with great accuracy.
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Notes
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Their code is available at https://github.com/nshafii/inesc_robotis_arm.
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Acknowledgements
This work is financed by the ERDF European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the FCT Fundao para a Ciłncia e a Tecnologia (Portuguese Foundation for Science and Technology) within project POCI-01-0145-FEDER-006961. P.C.M.A. Farias acknowledge support from CNPq/CsF PDE 233517/2014-6 for providing a scholarship.
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Shafii, N., Farias, P.C.M.A., Sousa, I., Sobreira, H., Reis, L.P., Moreira, A.P. (2017). Autonomous Interactive Object Manipulation and Navigation Capabilities for an Intelligent Wheelchair. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_39
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