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			<titleStmt><title level='a'>RangedIK: An Optimization-based Robot Motion Generation Method for Ranged-Goal Tasks</title></titleStmt>
			<publicationStmt>
				<publisher>IEEE</publisher>
				<date>05/29/2023</date>
			</publicationStmt>
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				<bibl> 
					<idno type="par_id">10475939</idno>
					<idno type="doi">10.1109/ICRA48891.2023.10161311</idno>
					
					<author>Yeping Wang</author><author>Pragathi Praveena</author><author>Daniel Rakita</author><author>Michael Gleicher</author>
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			<abstract><ab><![CDATA[Generating feasible robot motions in real-time requires achieving multiple tasks (i.e., kinematic requirements) simultaneously. These tasks can have a specific goal, a range of equally valid goals, or a range of acceptable goals with a preference toward a specific goal. To satisfy multiple and potentially competing tasks simultaneously, it is important to exploit the flexibility afforded by tasks with a range of goals. In this paper, we propose a real-time motion generation method that accommodates all three categories of tasks within a single, unified framework and leverages the flexibility of tasks with a range of goals to accommodate other tasks. Our method incorporates tasks in a weighted-sum multiple-objective optimization structure and uses barrier methods with novel loss functions to encode the valid range of a task. We demonstrate the effectiveness of our method through a simulation experiment that compares it to state-of-the-art alternative approaches, and by demonstrating it on a physical camera-in-hand robot that shows that our method enables the robot to achieve smooth and feasible camera motions.]]></ab></abstract>
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