Learning partially contracting dynamical systems from demonstrations
An algorithm for learning the dynamics of point-to-point motions from demonstrations using
an autonomous nonlinear dynamical system, named contracting dynamical system …
an autonomous nonlinear dynamical system, named contracting dynamical system …
Model-based reinforcement learning with parametrized physical models and optimism-driven exploration
In this paper, we present a robotic model-based reinforcement learning method that
combines ideas from model identification and model predictive control. We use a feature …
combines ideas from model identification and model predictive control. We use a feature …
Multicontroller positioning strategy for a pneumatic servo system via pressure feedback
L Zhao, Y Xia, Y Yang, Z Liu - IEEE Transactions on Industrial …, 2017 - ieeexplore.ieee.org
A backstepping-based controller is designed to improve positioning speed of a pneumatic
servo system by pressure feedback. A least-square method is used to identify parameters for …
servo system by pressure feedback. A least-square method is used to identify parameters for …
Learning position and orientation dynamics from demonstrations via contraction analysis
HC Ravichandar, A Dani - Autonomous Robots, 2019 - Springer
This paper presents a unified framework of model-learning algorithms, called contracting
dynamical system primitives (CDSP), that can be used to learn pose (ie, position and …
dynamical system primitives (CDSP), that can be used to learn pose (ie, position and …
Learning contracting nonlinear dynamics from human demonstration for robot motion planning
H Ravichandar, A Dani - Dynamic Systems …, 2015 - asmedigitalcollection.asme.org
In this paper, we present an algorithm to learn the dynamics of human arm motion from the
data collected from human actions. Learning the motion plans from human demonstrations …
data collected from human actions. Learning the motion plans from human demonstrations …
Human intention inference through interacting multiple model filtering
H chaandar Ravichandar, A Dani - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
We present an algorithm to learn human arm motion from demonstrations and infer the goal
location (intention) of human reaching actions. To capture the complexity of human arm …
location (intention) of human reaching actions. To capture the complexity of human arm …
Human intention inference and motion modeling using approximate em with online learning
HC Ravichandar, A Dani - 2015 IEEE/RSJ International …, 2015 - ieeexplore.ieee.org
In this paper, we present an algorithm to infer the intent of a human operator's arm
movements based on the observations from a Microsoft Kinect sensor. Intentions are …
movements based on the observations from a Microsoft Kinect sensor. Intentions are …
Active sampling based safe identification of dynamical systems using extreme learning machines and barrier certificates
Learning the dynamical system (DS) model from data that preserves dynamical system
properties is an important problem in many robot learning applications. Typically, the joint …
properties is an important problem in many robot learning applications. Typically, the joint …
Learning first principles systems knowledge from data: Stability and safety with applications to learning from demonstration
The chapter presents two methods of constrained learning of dynamical system models from
data with applications to learning from demonstration (LfD) or imitation learning in the …
data with applications to learning from demonstration (LfD) or imitation learning in the …
Learning periodic motions from human demonstrations using transverse contraction analysis
H chaandar Ravichandar… - 2016 American …, 2016 - ieeexplore.ieee.org
In this paper, an algorithm called transverse contracting dynamic system primitive (CDSP) to
learn the dynamics of periodic motions from demonstrations is presented. Learning motion …
learn the dynamics of periodic motions from demonstrations is presented. Learning motion …