Safety bounds in human robot interaction: A survey
In the era of industrialization and automation, safety is a critical factor that should be
considered during the design and realization of each new system that targets operation in …
considered during the design and realization of each new system that targets operation in …
A review of robotic assembly strategies for the full operation procedure: planning, execution and evaluation
Y Jiang, Z Huang, B Yang, W Yang - Robotics and Computer-Integrated …, 2022 - Elsevier
The application of robots in mechanical assembly increases the efficiency of industrial
production. With the requirements of flexible manufacturing, it has become a research …
production. With the requirements of flexible manufacturing, it has become a research …
Robot learning in the era of foundation models: A survey
The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …
Recent advances of deep robotic affordance learning: a reinforcement learning perspective
As a popular concept proposed in the field of psychology, affordance has been regarded as
one of the important abilities that enable humans to understand and interact with the …
one of the important abilities that enable humans to understand and interact with the …
The kit bimanual manipulation dataset
Learning models of bimanual manipulation tasks from human demonstration requires
capturing human body and hand motions, as well as the objects involved in the …
capturing human body and hand motions, as well as the objects involved in the …
Robot gaining accurate pouring skills through self-supervised learning and generalization
Pouring is one of the most commonly executed tasks in humans' daily lives, whose accuracy
is affected by multiple factors, including the type of material to be poured and the geometry …
is affected by multiple factors, including the type of material to be poured and the geometry …
A review of recurrent neural network architecture for sequence learning: Comparison between LSTM and GRU
S Nosouhian, F Nosouhian, AK Khoshouei - 2021 - preprints.org
Deep neural networks (DNNs) have made a huge impact in the field of machine learning by
providing unbeatable humanlike performance to solve real-world problems such as image …
providing unbeatable humanlike performance to solve real-world problems such as image …
The effects of selected object features on a pick-and-place task: A human multimodal dataset
We propose a dataset to study the influence of object-specific characteristics on human pick-
and-place movements and compare the quality of the motion kinematics extracted by …
and-place movements and compare the quality of the motion kinematics extracted by …
Learning instance-level n-ary semantic knowledge at scale for robots operating in everyday environments
Robots operating in everyday environments need to effectively perceive, model, and infer
semantic properties of objects. Existing knowledge reasoning frameworks only model binary …
semantic properties of objects. Existing knowledge reasoning frameworks only model binary …