About this Research Topic
This Research Topic has been realized in collaboration with Dr. Mohammed Aquil Maud Mirza of Bharat Institute of Engineering and Technology (BIET), India.
With the development of robotics, it is gradually becoming affordable to accommodate robots at home to enhance the automation of our daily lives. This new trend brings various challenges to the field of robotics: home robots frequently interact with humans, making the issue of safety, the design of human-robot interaction, the self-learning of robots in highly unstructured environments, and ubiquitous sensing in home environments challenging topics. Home robots need to be affordable, sometimes by sacrificing performance, making it a challenging topic to enhance robotic control accuracy through neural network based learning control, recurrent neural network based feedback control, long-short term memory reinforcement learning, etc.
Facing the challenges that have arisen due to the allocation of robots in home environments, this Research Topic aims to provide a timely forum for research on robot-enhanced home automation and to accelerate academic activities in related areas. This Research Topic is expected to report state-of-the-art studies in the field and encourage further novel developments in the field of robot-assisted home automation. We are particularly interested in, but do not limit the scope of submissions to, the following topics:
• Service robots, massaging robots, entertainment robots, home-
based surgical robots
• Human-robot interaction at home, robot grasping at home, home
modeling for robot navigation
• Service robot inter-cooperation, elderly companion robots, elderly
assistance robots, wearable exoskeletons
• Robot indoor navigation and manipulation, robot cooking, internet
of robots, home robot calibration
• Deep neural networks for home scene recognition, machine
learning for service robot skill training, personalized AI for
customized home environments, LSTM neural networks for robot
behavior learning, deep reinforcement learning for robot co-
• Convergence, stability, estimation, and observation in home
environments, cloud-based AI sharing
• AI-based home mapping, human-like home navigation, big data
analytics and fusion of large volumes of sensing data
• Sensor fusion of home data, AI-based home privacy, meta-
optimization, e.g., GA, PSO, -based home optimization
All submissions to this Research Topic must demonstrate the applicability of the proposed methods and technologies to human-robot interaction. For example, research on human language understanding must be contextualized in domestic human-robot interaction scenarios.
Keywords: Home Automation, Smart Home, Service Robots, Intelligent Space, Internet of Robots, Human In The Loop, Human-Robot Interaction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.