Abstract-This paper deals with the development of a visionbased controller for a continuum robot architecture. More precisely, the controlled robotic structure is based on threetube concentric tube robot (CTR), an emerging paradigm to design accurate, miniaturized, and flexible endoscopic robots. This approach has grown considerably in the recent years finding applications in numerous surgical disciplines. In contrast to conventional robotic structures, CTR kinematics arise many challenges for an optimal control such as friction, torsion, shear, and non-linear constitutive behavior. In fact, in order to ensure efficient and reliable control, in addition to computing an analytical and complete kinematic model, it is also important to close the control loop. To do this, we developed an eye-in-hand visual servoing scheme using a millimeter-sized camera embedded at the robot's tip.Both the kinematic model and the visual servoing controller were successfully validated in simulation with ViSP (Visual Servoing Platform) and using an experimental setup. The obtained results showed satisfactory performances for 3-degrees of freedom positioning and path following tasks with adaptive gain control.
Estimation of 3D object position is a crucial step for a variety of robotics and computer vision applications including 3D reconstruction and object manipulation. When working in microscale, new types of visual sensors are used such as Scanning Electron Microscope (SEM). Nowadays, microand nanomanipulation tasks, namely components assembly, are performed in teleoperated mode in most of the cases. Measuring object position and orientation is a crucial step towards automatic object handling. Current methods of pose estimation in SEM allow recovering full object movement using its computer-aided design (CAD) model. If the model is not known, most methods allow to estimate only in-plane translations and rotation around camera optical axis. In the literature, SEM is considered as a camera with parallel projection or an affine camera, which means image invariance to z-movement and bas-relief ambiguity. In this paper, authors address the problem of measuring full 3D rotation of the unknown scene for uncalibrated SEM without additional sensors. Rotations are estimated from image triplets by solving a spherical triangle from fundamental matrices only, without need of intrinsic calibration, allowing to avoid parallel projection ambiguities. The presented results, obtained in simulation and on real data, allow validating the proposed scheme.
This paper deals with the development of a visionbased control scheme for 3D laser steering. It proposes to incorporate a simplified trifocal constraint inside a path following scheme in order to ensure intuitively a 3D control of laser spot displacements in unknown environment (target). The described controller is obtained without complex mathematical formulation nor matrix inversion as it requires only weak camera and hand-eye calibration. The developed control law was validated in both simulation and experimental conditions using various scenarios (e.g., static and deformable 3D scenes, different control gains, initial velocities, etc.). The obtained results exhibit good accuracy and robustness with respect to the calibration and measurement errors and scene variations. In addition, with this kind of laser beam steering controller, it becomes possible to perfectly decouple the laser spot velocity from both the path shape and time. These features can fit several industrial applications (welding, micromachining, etc.) as well as surgical purposes (e.g., laser surgery) requirements. • a geometric task, which consists of approaching the robot to the desired curve, • a dynamic assignment task, which assigns a velocity profile (instead of time) to the desired curve.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.