Robot learning from randomized simulations: A review
The rise of deep learning has caused a paradigm shift in robotics research, favoring
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
Digital twin for human–robot collaboration in manufacturing: Review and outlook
AK Ramasubramanian, R Mathew, M Kelly… - Applied Sciences, 2022 - mdpi.com
Industry 4.0, as an enabler of smart factories, focuses on flexible automation and
customization of products by utilizing technologies such as the Internet of Things and cyber …
customization of products by utilizing technologies such as the Internet of Things and cyber …
Interventional causal representation learning
Causal representation learning seeks to extract high-level latent factors from low-level
sensory data. Most existing methods rely on observational data and structural assumptions …
sensory data. Most existing methods rely on observational data and structural assumptions …
[HTML][HTML] Robotic assembly of timber joints using reinforcement learning
In architectural construction, automated robotic assembly is challenging due to occurring
tolerances, small series production and complex contact situations, especially in assembly …
tolerances, small series production and complex contact situations, especially in assembly …
The role of physics-based simulators in robotics
Physics-based simulation provides an accelerated and safe avenue for developing,
verifying, and testing robotic control algorithms and prototype designs. In the quest to …
verifying, and testing robotic control algorithms and prototype designs. In the quest to …
[HTML][HTML] Offline reinforcement learning for industrial process control: A case study from steel industry
Flatness is a crucial indicator of strip quality that presents a challenge in regulation due to
the high-speed process and the nonlinear relationship between flatness and process …
the high-speed process and the nonlinear relationship between flatness and process …
Generator identification for linear SDEs with additive and multiplicative noise
Y Wang, X Geng, W Huang… - Advances in Neural …, 2024 - proceedings.neurips.cc
In this paper, we present conditions for identifying the generator of a linear stochastic
differential equation (SDE) from the distribution of its solution process with a given fixed …
differential equation (SDE) from the distribution of its solution process with a given fixed …
ROS-PyBullet Interface: A framework for reliable contact simulation and human-robot interaction
Reliable contact simulation plays a key role in the development of (semi-) autonomous
robots, especially when dealing with contact-rich manipulation scenarios, an active robotics …
robots, especially when dealing with contact-rich manipulation scenarios, an active robotics …
Learning to fold real garments with one arm: A case study in cloud-based robotics research
Autonomous fabric manipulation is a longstanding challenge in robotics, but evaluating
progress is difficult due to the cost and diversity of robot hardware. Using Reach, a cloud …
progress is difficult due to the cost and diversity of robot hardware. Using Reach, a cloud …
Benchmarking simulated robotic manipulation through a real world dataset
J Collins, J McVicar, D Wedlock… - IEEE Robotics and …, 2019 - ieeexplore.ieee.org
We present a benchmark to facilitate simulated manipulation; an attempt to overcome the
obstacles of physical benchmarks through the distribution of a real world, ground truth …
obstacles of physical benchmarks through the distribution of a real world, ground truth …