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This paper introduces a new model for robot behavior categorization.
In this paper, we propose and investigate a new model for robot navigation in large unstructured environments.
Based on these researches, we have developed the basic structure to realize the cognitive model for robot partners that interact with humans.
Gockley et al. [12] proposed a model for robot to follow person in the direction of the person and evaluated the model to be a human-like behavior.
We first build a generic kinematic model for robot structure error analysis using a Denavit–Hartenberg transformation matrix, differential changes for this transformation matrix and link parameters.
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"Real‑time data distribution model for robots" section proposes a real-time data distribution model for robots.
A loosely coupled data publish-subscribe model for robots is proposed firstly.
Therefore, four kinds of time-related QoS parameters are supported in our model: Fig. 3 Real-time data distribution model for robots.
To realize this goal, as shown in "Real‑time data distribution model for robots" section, two kinds of topics are strictly distinguished in our data distribution model, and the APIs of the general topic are identical with those in ROS.
To avoid confusing the users of micROS-drt with those complex policies, micROS-drt chooses not to directly expose the DDS APIs directly and introduces a more practical and simplified real-time data distribution model (cf. Sect. "Real‑time data distribution model for robots") instead.
Cerebellar models have long been advocated as viable models for robot dynamics control.
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