Generating motion for robots that interact with objects of various shape...
In this work, we propose to learn robot geometry as distance fields (RDF...
Robot programming tools ranging from inverse kinematics (IK) to model
pr...
This paper presents a whole-body robot control method for exploring and
...
Soft object manipulation tasks in domestic scenes pose a significant
cha...
Planning multi-contact motions in a receding horizon fashion requires a ...
Long-term non-prehensile planar manipulation is a challenging task for
p...
Long-term non-prehensile planar manipulation is a challenging task for r...
Many problems in robotics are fundamentally problems of geometry, which ...
Achieving reactive robot behavior in complex dynamic environments is sti...
Optimal control in robotics has been increasingly popular in recent year...
The convergence of many numerical optimization techniques is highly sens...
This letter describes an approach to achieve well-known Chinese cooking ...
Daily manipulation tasks are characterized by regular characteristics
as...
Robot programming methods for industrial robots are time consuming and o...
This chapter presents an overview of techniques used for the analysis,
e...
By generating control policies that create natural search behaviors in
a...
Optimal control is often used in robotics for planning a trajectory to
a...
Mapping operator motions to a robot is a key problem in teleoperation. D...
In high dimensional robotic system, the manifold of the valid configurat...
In learning from demonstrations, many generative models of trajectories ...
Collaborative robots offer increased interaction capabilities at relativ...
Probability distributions are key components of many learning from
demon...
Learning from demonstration (LfD) is an intuitive framework allowing
non...
Humans exhibit outstanding learning, planning and adaptation capabilitie...
This paper proposes an inverse reinforcement learning (IRL) framework to...
This study proposes a novel imitation learning approach for the stochast...
This paper addresses the problem of efficiently achieving visual predict...
This paper addresses the problem of efficiently achieving visual predict...
In this paper, we propose a framework to build a memory of motion to
war...
In learning from demonstrations, it is often desirable to adapt the beha...
Bayesian optimization (BO) recently became popular in robotics to optimi...
This paper presents an overview of robot learning and adaptive control
a...
Trajectory optimization for motion planning requires a good initial gues...
Robotic tasks can be accomplished by exploiting different forms of
redun...
We propose a method to approximate the distribution of robot configurati...
A common approach to learn robotic skills is to imitate a policy demonst...
When data are organized in matrices or arrays of higher dimensions (tens...
In this paper we show how different choices regarding compliance affect ...
Body posture influences human and robots performance in manipulation tas...
Generalizing manipulation skills to new situations requires extracting
i...
Most policy search algorithms require thousands of training episodes to ...
Torque controllers have become commonplace in the new generation of robo...