Publication

Bimanual Skill Learning with Pose and Joint Space Constraints

Related publications (34)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Implicit Distance Functions: Learning and Applications in Robotics

Mikhail Koptev

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

EPFL2023

Learning from demonstration using products of experts: Applications to manipulation and task prioritization

Sylvain Calinon, Emmanuel Pignat

Probability distributions are key components of many learning from demonstration (LfD) approaches, with the spaces chosen to represent tasks playing a central role. Although the robot configuration is defined by its joint angles, end-effector poses are oft ...

SAGE PUBLICATIONS LTD2021

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez

In this letter, we propose a real-time self-collision avoidance approach for whole-body humanoid robot control. To achieve this, we learn the feasible regions of control in the humanoid's joint space as smooth self-collision boundary functions. Collision-f ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Beyond Soft Hands: Efficient Grasping With Non-Anthropomorphic Soft Grippers

Yufei Hao

Grasping and manipulation are challenging tasks that are nonetheless critical for many robotic systems and applications. A century ago, robots were conceived as humanoid automata. While conceptual at the time, this viewpoint remains influential today. Many ...

FRONTIERS MEDIA SA2021

Learning Task Priorities from Demonstrations

Sylvain Calinon

As humanoid robots become increasingly popular, learning and control algorithms must take into account the new constraints and challenges inherent to these platforms, if we aim to fully exploit their potential. One of the most prominent of such aspects is ...

2019

Object Grasping of Humanoid Robot Based on YOLO

Daniel Thalmann

This paper presents a system that aims to achieve autonomous grasping for micro-controller based humanoid robots such as the Inmoov robot [1]. The system consists of a visual sensor, a central controller and a manipulator. We modify the open sourced object ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Learning Control

Sylvain Calinon

This chapter presents an overview of learning approaches for the acquisition of controllers and movement skills in humanoid robots. The term learning control refers to the process of acquiring a control strategy to achieve a task. While the definition is i ...

Springer2019

SCALAR: Simultaneous Calibration of 2-D Laser and Robot Kinematic Parameters Using Planarity and Distance Constraints

Teguh Santoso Lembono

In this paper, we propose SCALAR, a calibration method to simultaneously calibrate the kinematic parameters of a 6-DoF robot and the extrinsic parameters of a 2-D laser range finder (LRF) attached to the robot's flange. The calibration setup requires only ...

2019

Learning Control

Sylvain Calinon

Springer2018

A singularity-tolerant inverse kinematics including joint position and velocity limitations

Auke Ijspeert, Salman Faraji

Humanoid robots have many degrees of freedom which ideally enables them to accomplish different tasks. From a control viewpoint, however, the geometric complexity makes planning and control difficult. Favoring controllability properties, it is popular to o ...

2017