Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Bekiroglu, Yasemin"'
Grasping is a fundamental skill for robots to interact with their environment. While grasp execution requires coordinated movement of the hand and arm to achieve a collision-free and secure grip, many grasp synthesis studies address arm and hand moti
Externí odkaz:
http://arxiv.org/abs/2309.16085
Autor:
Cosier, Lucas, Iordan, Rares, Zwane, Sicelukwanda, Franzese, Giovanni, Wilson, James T., Deisenroth, Marc Peter, Terenin, Alexander, Bekiroglu, Yasemin
Publikováno v:
Artificial Intelligence and Statistics, 2024
To control how a robot moves, motion planning algorithms must compute paths in high-dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obstacles, and prevent
Externí odkaz:
http://arxiv.org/abs/2309.00854
Objects we interact with and manipulate often share similar parts, such as handles, that allow us to transfer our actions flexibly due to their shared functionality. This work addresses the problem of transferring a grasp experience or a demonstratio
Externí odkaz:
http://arxiv.org/abs/2308.07807
This paper presents a novel Learning from Demonstration (LfD) method that uses neural fields to learn new skills efficiently and accurately. It achieves this by utilizing a shared embedding to learn both scene and motion representations in a generati
Externí odkaz:
http://arxiv.org/abs/2308.05040
Efficient and accurate 3D object shape reconstruction contributes significantly to the success of a robot's physical interaction with its environment. Acquiring accurate shape information about unknown objects is challenging, especially in unstructur
Externí odkaz:
http://arxiv.org/abs/2308.00576
There are various trajectory planners for mobile manipulators. It is often challenging to compare their performance under similar circumstances due to differences in hardware, dissimilarity of tasks and objectives, as well as uncertainties in measure
Externí odkaz:
http://arxiv.org/abs/2211.01812
In this paper, we propose to use a nonlinear adaptive PID controller to regulate the joint variables of a mobile manipulator. The motion of the mobile base forces undue disturbances on the joint controllers of the manipulator. In designing a conventi
Externí odkaz:
http://arxiv.org/abs/2207.04866
Autor:
Gothoskar, Nishad, Lázaro-Gredilla, Miguel, Bekiroglu, Yasemin, Agarwal, Abhishek, Tenenbaum, Joshua B., Mansinghka, Vikash K., George, Dileep
Visual servoing enables robotic systems to perform accurate closed-loop control, which is required in many applications. However, existing methods either require precise calibration of the robot kinematic model and cameras or use neural architectures
Externí odkaz:
http://arxiv.org/abs/2202.03697
This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement to optimise grasp stability. In many situations, a robot will have only
Externí odkaz:
http://arxiv.org/abs/2103.00655
Autor:
Gothoskar, Nishad, Lázaro-Gredilla, Miguel, Agarwal, Abhishek, Bekiroglu, Yasemin, George, Dileep
We introduce a novel formulation for incorporating visual feedback in controlling robots. We define a generative model from actions to image observations of features on the end-effector. Inference in the model allows us to infer the robot state corre
Externí odkaz:
http://arxiv.org/abs/2003.04474