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Maintaining Visibility of Dynamic Objects in Cluttered Environments Using Mobile Manipulators and Vector Field Inequalities

Fatih Dursun, Bruno Vilhena Adorno, Simon Watson, Wei Pan

发表年份
2023
引用次数
2

摘要

Vision-based perception has become prevalent in robotic applications, especially in those where the control loop relies on visual data, such as visual servoing. For those applications, ensuring that the features or target object remain visible to the camera is critical, necessitating visibility-aware control. In this paper, we propose a method to guarantee the visibility of a dynamic object using a constrained kinematic controller and Vector Field Inequalities (VFIs) to include a linear visibility constraint. Unlike existing methods, we introduce constraints into the kinematic controller to ensure the target's visibility without needing a trajectory optimizer or local planner. Our method maintains the target object in the camera field of view (FoV) by representing the FoV with four infinite planes and maintaining the distance between the target object and each plane higher than a predefined distance. We evaluated the proposed approach using a mobile manipulator in two simulations involving cluttered environments: the first scenario involves a stationary target object, whereas the second scenario presents a more challenging workspace involving a moving target. Our results demonstrate that the proposed approach successfully maintains the target within the FoV while avoiding obstacles in the workspace, showing the potential of our method to improve the safety and reliability of visual-servoing-based robotic systems.

关键词

WorkspaceVisibilityVisual servoingComputer visionComputer scienceArtificial intelligenceController (irrigation)TrajectoryConstraint (computer-aided design)Kinematics

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