Symbol emergence in robotics: a survey
Humans can learn a language through physical interaction with their environment and
semiotic communication with other people. It is very important to obtain a computational …
semiotic communication with other people. It is very important to obtain a computational …
Bayesian and neural inference on lstm-based object recognition from tactile and kinesthetic information
F Pastor, J García-González… - IEEE Robotics and …, 2020 - ieeexplore.ieee.org
Recent advances in the field of intelligent robotic manipulation pursue providing robotic
hands with touch sensitivity. Haptic perception encompasses the sensing modalities …
hands with touch sensitivity. Haptic perception encompasses the sensing modalities …
Serket: An architecture for connecting stochastic models to realize a large-scale cognitive model
To realize human-like robot intelligence, a large-scale cognitive architecture is required for
robots to understand their environment through a variety of sensors with which they are …
robots to understand their environment through a variety of sensors with which they are …
Learning relational object categories using behavioral exploration and multimodal perception
This paper proposes a framework for learning human-provided category labels that describe
individual objects, pairwise object relationships, as well as groups of objects. The framework …
individual objects, pairwise object relationships, as well as groups of objects. The framework …
Compliant parametric dynamic movement primitives
In this paper, we propose and implement an advanced manipulation framework that enables
parametric learning of complex action trajectories along with their haptic feedback profiles …
parametric learning of complex action trajectories along with their haptic feedback profiles …
Online multimodal ensemble learning using self-learned sensorimotor representations
M Zambelli, Y Demirisy - IEEE Transactions on Cognitive and …, 2016 - ieeexplore.ieee.org
Internal models play a key role in cognitive agents by providing on the one hand predictions
of sensory consequences of motor commands (forward models), and on the other hand …
of sensory consequences of motor commands (forward models), and on the other hand …
Mutual learning of an object concept and language model based on MLDA and NPYLM
Humans develop their concept of an object by classifying it into a category, and acquire
language by interacting with others at the same time. Thus, the meaning of a word can be …
language by interacting with others at the same time. Thus, the meaning of a word can be …
Online learning of concepts and words using multimodal LDA and hierarchical Pitman-Yor Language Model
T Araki, T Nakamura, T Nagai… - 2012 IEEE/RSJ …, 2012 - ieeexplore.ieee.org
In this paper, we propose an online algorithm for multimodal categorization based on the
autonomously acquired multimodal information and partial words given by human users. For …
autonomously acquired multimodal information and partial words given by human users. For …
Open-environment robotic acoustic perception for object recognition
S Jin, H Liu, B Wang, F Sun - Frontiers in neurorobotics, 2019 - frontiersin.org
Object recognition in containers is extremely difficult for robots. Dynamic audio signals are
more responsive to an object's internal property. Therefore, we adopt the dynamic contact …
more responsive to an object's internal property. Therefore, we adopt the dynamic contact …
Online algorithm for robots to learn object concepts and language model
J Nishihara, T Nakamura… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Humans form concept of objects by classifying them into categories, and acquire language
by simultaneously interacting with others. Thus, the meaning of a word can be learned by …
by simultaneously interacting with others. Thus, the meaning of a word can be learned by …