Continuous Visual World Modeling for Autonomous Robot Manipulation
Autor: | Besim Ongun Kanat, Mustafa Ersen, Arda Inceoglu, Sanem Sariel, Cagatay Koc |
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Rok vydání: | 2019 |
Předmět: |
0209 industrial biotechnology
Service (systems architecture) Computer science media_common.quotation_subject 02 engineering and technology Object (computer science) Autonomous robot Computer Science Applications Variety (cybernetics) Visualization Human-Computer Interaction 020901 industrial engineering & automation Control and Systems Engineering Human–computer interaction Perception 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Electrical and Electronic Engineering Software media_common |
Zdroj: | IEEE Transactions on Systems, Man, and Cybernetics: Systems. 49:192-205 |
ISSN: | 2168-2232 2168-2216 |
Popis: | Service robots need to handle a variety of everyday manipulation tasks to accomplish household chores such as cooking and cleaning. Successful execution of these tasks is highly dependent on how reliable the robot perceives its environment through noisy sensing. We present a visual world modeling system for service robots to generate and maintain accurate models of their environments for continuous scenarios. This system is designed to provide a generic platform for both humanoid and ground manipulation robots using different types of vision sensors and algorithms. In our particular implementation, visual data processed by different perception algorithms are used for building and continuously updating a world model of the environment. We evaluate our system on a variety of object manipulation scenarios and show that the system produces consistent perception outcomes suitable for different manipulation tasks. |
Databáze: | OpenAIRE |
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