Towards open and expandable cognitive AI architectures for large-scale multi-agent human-robot collaborative learning
Learning from Demonstration (LfD) constitutes one of the most robust methodologies for
constructing efficient cognitive robotic systems. Despite the large body of research works …
constructing efficient cognitive robotic systems. Despite the large body of research works …
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks—A Reward Curriculum Approach
For years, the fully-automated robotic assembly has been a highly sought-after technology in
large-scale manufacturing. Yet it still struggles to find widespread implementation in …
large-scale manufacturing. Yet it still struggles to find widespread implementation in …
Robotic peg-in-hole assembly based on reversible dynamic movement primitives and trajectory optimization
Because of the complexity of interaction between the robot and the environment, robotic peg-
in-hole assembly has always been a hot research topic in the fields of robotics and …
in-hole assembly has always been a hot research topic in the fields of robotics and …
Dynamic robot assignment for flexible serial production systems
This letter aims at modeling and real-time control of a flexible manufacturing system (FMS)
that is operated by multi-skilled mobile robots. By introducing the idea of a unique ideal …
that is operated by multi-skilled mobile robots. By introducing the idea of a unique ideal …
Fuzzy dynamical system for robot learning motion skills from human demonstration
Learning from demonstration (LfD) is an intuitive strategy for transferring human motion skills
to robots in an agile and adaptable manner. The major goal of LfD is to identify significant …
to robots in an agile and adaptable manner. The major goal of LfD is to identify significant …
Performance evaluation of optical motion capture sensors for assembly motion capturing
The optical motion capture (MoCap) sensor provides an effective way to capture human
motions and transform them into valuable data that can be applied to certain tasks, eg robot …
motions and transform them into valuable data that can be applied to certain tasks, eg robot …
Trajectory-based skill learning for overhead construction robots using generalized cylinders with orientation
Overhead work involving the construction and maintenance of civil infrastructure (eg,
tunnels, overpasses, and buildings) is strenuous and fatigue-inducing for human workers …
tunnels, overpasses, and buildings) is strenuous and fatigue-inducing for human workers …
A human–robot collaboration method using a pose estimation network for robot learning of assembly manipulation trajectories from demonstration videos
The wide application of industrial robots has greatly improved assembly efficiency and
reliability. However, determining how to efficiently teach a robot to perform assembly …
reliability. However, determining how to efficiently teach a robot to perform assembly …
Encoding multiple sensor data for robotic learning skills from multimodal demonstration
Learning a task such as pushing something, where the constraints of both position and force
have to be satisfied, is usually difficult for a collaborative robot. In this work, we propose a …
have to be satisfied, is usually difficult for a collaborative robot. In this work, we propose a …
A task-learning strategy for robotic assembly tasks from human demonstrations
G Ding, Y Liu, X Zang, X Zhang, G Liu, J Zhao - Sensors, 2020 - mdpi.com
In manufacturing, traditional task pre-programming methods limit the efficiency of human–
robot skill transfer. This paper proposes a novel task-learning strategy, enabling robots to …
robot skill transfer. This paper proposes a novel task-learning strategy, enabling robots to …