Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Pointing in depth is shaped by a natural grasping distance prior

View through CrossRef
Abstract Vision in depth is distorted. A similar distortion can be observed for pointing to visual targets in depth. It has been suggested that pointing errors in depth reflect the visual distortion. However, much research has suggested that in case visual information is not rich enough, the sensorimotor system involves prior knowledge to optimally plan movement trajectories. Here, we show that pointing in depth is guided by a prior that biases movements toward the natural grasping distance at which object manipulation is usually performed. To dissociate whether pointing is guided by distorted vision only or whether it takes into account a natural grasping distance prior, we adapted pointing movements. Participants received visual feedback about the success of their pointing once the movement was finished. We distorted the feedback to signal either that pointing was not far enough or in separate sessions that pointing was too far. Participants adapted to this artificial error by either extending or shortening their pointing movements. The generalization of pointing adaptation revealed a bias in movement planning that is inconsistent with pointing being guided only by distorted vision but with the involvement of knowledge about the natural grasping distance. Adaptation was strongest for pointing movements to a middle position that corresponds to the natural grassing distance and it was weakest for movements leading away from it. It has been demonstrated that pointing adaptation in depth changes visual perception (Volcic et al., 2013). We also wondered how effects of pointing adaptation on visual space would generalize in depth.
Title: Pointing in depth is shaped by a natural grasping distance prior
Description:
Abstract Vision in depth is distorted.
A similar distortion can be observed for pointing to visual targets in depth.
It has been suggested that pointing errors in depth reflect the visual distortion.
However, much research has suggested that in case visual information is not rich enough, the sensorimotor system involves prior knowledge to optimally plan movement trajectories.
Here, we show that pointing in depth is guided by a prior that biases movements toward the natural grasping distance at which object manipulation is usually performed.
To dissociate whether pointing is guided by distorted vision only or whether it takes into account a natural grasping distance prior, we adapted pointing movements.
Participants received visual feedback about the success of their pointing once the movement was finished.
We distorted the feedback to signal either that pointing was not far enough or in separate sessions that pointing was too far.
Participants adapted to this artificial error by either extending or shortening their pointing movements.
The generalization of pointing adaptation revealed a bias in movement planning that is inconsistent with pointing being guided only by distorted vision but with the involvement of knowledge about the natural grasping distance.
Adaptation was strongest for pointing movements to a middle position that corresponds to the natural grassing distance and it was weakest for movements leading away from it.
It has been demonstrated that pointing adaptation in depth changes visual perception (Volcic et al.
, 2013).
We also wondered how effects of pointing adaptation on visual space would generalize in depth.

Related Results

Perancangan Kontroler Pointing Antena Yagi pada Frekuensi Radio Berbasis Mikrokontroler
Perancangan Kontroler Pointing Antena Yagi pada Frekuensi Radio Berbasis Mikrokontroler
Abstrak--Pada sistem komunikasi nirkabel yang menggunakan antena, arah antena pusat memegang peranan penting. Hal ini dikarenakan penyimpangan arah antena mempengaruhi kinerja komu...
A lightweight grasping pose estimation method for retail warehousing
A lightweight grasping pose estimation method for retail warehousing
Abstract Robotic grasping has been widely used in various industries. How to meet the requirements of grasping accuracy and grasping speed at the same time is a challenging...
An efficient pose classification method for robotic grasping
An efficient pose classification method for robotic grasping
Background: The unstructured environment, the different geometric shapes of objects, and the uncertainty of sensor noise have brought many challenges to robotic...
Bone indicators of grasping hands in lizards
Bone indicators of grasping hands in lizards
Grasping is one of a few adaptive mechanisms that, in conjunction with clinging, hooking, arm swinging, adhering, and flying, allowed for incursion into the arboreal eco-space. Lit...
The causal role of three frontal cortical areas in grasping
The causal role of three frontal cortical areas in grasping
Abstract Efficient object grasping requires the continuous control of arm and hand movements based on visual information. Previous studies have identified a network...
Precise Measurement of Grasping Force for Noncollaborative Infants
Precise Measurement of Grasping Force for Noncollaborative Infants
AbstractAmong the medical parameters used for infants, the grasping force is particularly important because it indicates their musculoskeletal and neurological development. Althoug...
Learning-based robotic grasping: A review
Learning-based robotic grasping: A review
As personalization technology increasingly orchestrates individualized shopping or marketing experiences in industries such as logistics, fast-moving consumer goods, and food deliv...
Visual inspection and grasping methods based on deep learning
Visual inspection and grasping methods based on deep learning
Aiming at the problems of existing robot grasping systems that have high hardware requirements, are difficult to adapt to different objects, and produce large harmful torques durin...

Back to Top