End-of-life electric vehicle battery disassembly enabled by intelligent and human-robot collaboration technologies: A review
Electric vehicles (EVs) have been experiencing radical growth to embrace the ambitious
targets of decarbonisation and circular economies. The trend has led to a significant surge in …
targets of decarbonisation and circular economies. The trend has led to a significant surge in …
Learning belief representations for partially observable deep RL
Many important real-world Reinforcement Learning (RL) problems involve partial
observability and require policies with memory. Unfortunately, standard deep RL algorithms …
observability and require policies with memory. Unfortunately, standard deep RL algorithms …
Adaptive robotic information gathering via non-stationary Gaussian processes
Robotic Information Gathering (RIG) is a foundational research topic that answers how a
robot (team) collects informative data to efficiently build an accurate model of an unknown …
robot (team) collects informative data to efficiently build an accurate model of an unknown …
A Review on Robot Manipulation Methods in Human-Robot Interactions
Robot manipulation is an important part of human-robot interaction technology. However,
traditional pre-programmed methods can only accomplish simple and repetitive tasks. To …
traditional pre-programmed methods can only accomplish simple and repetitive tasks. To …
Learning-Based Control for Soft Robot–Environment Interaction with Force/Position Tracking Capability
Soft robotics promises to achieve safe and efficient interactions with the environment by
exploiting its inherent compliance and designing control strategies. However, effective …
exploiting its inherent compliance and designing control strategies. However, effective …
BetaZero: Belief-state planning for long-horizon POMDPs using learned approximations
Real-world planning problems $\unicode {x2014} $ including autonomous driving and
sustainable energy applications like carbon storage and resource exploration $\unicode …
sustainable energy applications like carbon storage and resource exploration $\unicode …
Digital twin-enabled domain adaptation for zero-touch UAV networks: Survey and challenges
In existing wireless networks, the control programs have been designed manually and for
certain predefined scenarios. This process is complicated and error-prone, and the resulting …
certain predefined scenarios. This process is complicated and error-prone, and the resulting …
[HTML][HTML] Energy management of a microgrid considering nonlinear losses in batteries through Deep Reinforcement Learning
D Domínguez-Barbero, J García-González… - Applied Energy, 2024 - Elsevier
The massive deployment of microgrids could play a significant role in achieving
decarbonization of the electric sector amid the ongoing energy transition. The effective …
decarbonization of the electric sector amid the ongoing energy transition. The effective …
[HTML][HTML] Learning-based methods for adaptive informative path planning
Abstract adaptive informative path planning (AIPP) is important to many robotics
applications, enabling mobile robots to efficiently collect useful data about initially unknown …
applications, enabling mobile robots to efficiently collect useful data about initially unknown …
Offline Risk-sensitive RL with Partial Observability to Enhance Performance in Human-Robot Teaming
The integration of physiological computing into mixed-initiative human-robot interaction
systems offers valuable advantages in autonomous task allocation by incorporating real …
systems offers valuable advantages in autonomous task allocation by incorporating real …