In order to meaningfully interact with the world, robot manipulators mus...
Real-time synthesis of legged locomotion maneuvers in challenging indust...
This paper proposes a simple strategy for sim-to-real in Deep-Reinforcem...
Motion planning framed as optimisation in structured latent spaces has
r...
We present a novel approach to path planning for robotic manipulators, i...
Robotic locomotion is often approached with the goal of maximizing robus...
Training deep reinforcement learning (DRL) locomotion policies often req...
Quadruped locomotion is rapidly maturing to a degree where robots now
ro...
Object pose estimation is an important component of most vision pipeline...
Achieving agile maneuvers through multiple contact phases has been a
lon...
Deployment of robotic systems in the real world requires a certain level...
Online planning of whole-body motions for legged robots is challenging d...
Over the years, the separate fields of motion planning, mapping, and hum...
Quadruped locomotion is rapidly maturing to a degree where robots now
ro...
Object rearrangement has recently emerged as a key competency in robot
m...
As robots operate in increasingly complex and dynamic environments, fast...
In this paper we explore the use of block coordinate descent (BCD) to
op...
Haptic interaction is essential for the dynamic dexterity of animals, wh...
To dynamically traverse challenging terrain, legged robots need to
conti...
End-to-end visuomotor control is emerging as a compelling solution for r...
Recent work has demonstrated real-time mapping and reconstruction from d...
Central Pattern Generators (CPGs) have several properties desirable for
...
We present a unified model-based and data-driven approach for quadrupeda...
Optimal control is a popular approach to synthesize highly dynamic motio...
Path planning and collision avoidance are challenging in complex and hig...
Benchmarks of state-of-the-art rigid-body dynamics libraries have report...
Shooting methods are an efficient approach to solving nonlinear optimal
...
We present a novel framework for motion planning in dynamic environments...
Traditional approaches to quadruped control frequently employ simplified...
Planning whole-body motions while taking into account the terrain condit...
Deep reinforcement learning (RL) uses model-free techniques to optimize
...
Dynamic traversal of uneven terrain is a major objective in the field of...
Despite the great progress in quadrupedal robotics during the last decad...
Most animal and human locomotion behaviors for solving complex tasks inv...
We present a framework for dynamic quadrupedal locomotion over challengi...
We present a legged motion planning approach for quadrupedal locomotion ...