Learning inverse kinematics and dynamics of a robotic manipulator using generative adversarial networks
H Ren, P Ben-Tzvi - Robotics and Autonomous Systems, 2020 - Elsevier
Obtaining inverse kinematics and dynamics of a robotic manipulator is often crucial for robot
control. Analytical models are typically used to approximate real robot systems, and various …
control. Analytical models are typically used to approximate real robot systems, and various …
Goal-directed tactile exploration for body model learning through self-touch on a humanoid robot
An early integration of tactile sensing into motor coordination is the norm in animals, but still
a challenge for robots. Tactile exploration through touches on the body gives rise to first …
a challenge for robots. Tactile exploration through touches on the body gives rise to first …
Intelligent Control of Robots with Minimal Power Consumption in Pick-and-Place Operations
In many industries, such as assembling, welding, packaging, quality control, loading, and
wrapping, a specific operation is requested, which is to pick processed objects in a given …
wrapping, a specific operation is requested, which is to pick processed objects in a given …
Interest-driven exploration with observational learning for developmental robots
It has been emphasized for a long time that real-world applications of developmental robots
require lifelong and online learning. A major challenge in this field is the high sample …
require lifelong and online learning. A major challenge in this field is the high sample …
Efficient online interest-driven exploration for developmental robots
A major challenge for online and data-driven model learning in robotics is the high sample
complexity. This hinders its efficiency and practical feasibility for lifelong learning, in …
complexity. This hinders its efficiency and practical feasibility for lifelong learning, in …
Active inverse model learning with error and reachable set estimates
D Driess, S Schmitt, M Toussaint - 2019 IEEE/RSJ International …, 2019 - ieeexplore.ieee.org
In this work, we propose a framework to learn an inverse model of redundant systems. We
address three problems. By formalizing what it actually means to learn an inverse model, we …
address three problems. By formalizing what it actually means to learn an inverse model, we …
Hierarchical interest-driven goal babbling for efficient bootstrapping of sensorimotor skills
We propose a novel hierarchical online learning scheme for fast and efficient bootstrapping
of sensorimotor skills. Our scheme permits rapid data-driven robot model learning in a" …
of sensorimotor skills. Our scheme permits rapid data-driven robot model learning in a" …
Data-Driven Estimation of Forces Along the Backbone of Concentric Tube Continuum Robots
Concentric tube continuum robots (CTCRs) belong to the family of continuum robots with
applications in minimally invasive surgeries. Because of this application domain, measuring …
applications in minimally invasive surgeries. Because of this application domain, measuring …
Control of Pick-and-Place Robots with Reduced Power Consumption
V Vodovozov, Z Raud… - 2023 IEEE 64th …, 2023 - ieeexplore.ieee.org
In such industries as assembling, welding, packaging, quality control, loading, and
wrapping, the specific robot operation is requested, which is to pick processing objects to a …
wrapping, the specific robot operation is requested, which is to pick processing objects to a …
Online associative multi-stage goal babbling toward versatile learning of sensorimotor skills
We develop an online learning scheme inspired by the versatility of the human learning
system to bootstrap several sensorimotor skills in “Learning while Behaving” fashion. Our …
system to bootstrap several sensorimotor skills in “Learning while Behaving” fashion. Our …