Sentence examples for manipulation action from inspiring English sources

We create a new manipulation action benchmark with 8 different manipulation tasks including in total 120 samples to learn an archetypal SEC model for each manipulation action.

In some cases, additional codes can also be evoked, such as motor-related properties of the represented object, where contextual information related to the object's functional intention and manipulation action may also be processed automatically when reading the word.

This stream seems to be involved in representing objects or their features both at an abstract-cognitive level (memory) as well as in the context of potential fine motor requirements for manipulation (action).

Insider trading actions increased 25% and market manipulation actions increased 45%.

This supports the notion that SECs are a useful tool for classifying manipulation actions in a fully automatic way.

In this paper we present a hierarchical framework for representation of manipulation actions and its applicability to the problem of top down action extraction from observation.

Understanding and learning the semantics of complex manipulation actions are intriguing and non-trivial issues for the development of autonomous robots.

In this paper, we introduce our methods for sensor calibration and 3D data segmentation to use it to automatically plan grasps and manipulation actions for a service robot.

In this paper, we present a novel method for an on-line, incremental learning of the semantics of manipulation actions by observation.

In this work, we have designed, implemented, and analyzed a framework that allows us to envision the physical effects of robot manipulation actions.

We here show that the SEC concept can be used to bootstrap the learning of the semantics of manipulation actions without using any prior knowledge about actions or objects.