Media Summary: An overview of our 2021 IROS paper ( finding the optimal locations to ... Supplementary video of our work: RangedIK: An A path planner using operator inputs to generate a feasible path. The simulation is conducted using ROS Rviz.

Optimization Based Robot Team Exploration - Detailed Analysis & Overview

An overview of our 2021 IROS paper ( finding the optimal locations to ... Supplementary video of our work: RangedIK: An A path planner using operator inputs to generate a feasible path. The simulation is conducted using ROS Rviz. This video addresses the problem of real-time planning and control of a The video demonstrates our algorithms for More information can be found in the following publications: D. Sun, Alexander Kleiner and C. Schindelhauer. 2010.

Siyuan Feng, X Xinjilefu, Christopher G. Atkeson and Joohyung Kim. Reconnaissance and Exploration with a autonomous Multi Robot Team

Photo Gallery

Optimization-Based Robot Team Exploration Considering Attrition and Communication Constraints
RangedIK: An Optimization-based Robot Motion Generation Method for Ranged-Goal Tasks
Optimization-based Robot Path Planning using Quadratic Programming
Multi-robot Exploration with Custom RRT* and homotopy classes trajectory optimization integration
Field Exploration Robots with ACO algorithm - ACO Robots - Maker Faire Rome 2020
Path Planning with Multiple Rapidly-exploring Random Trees for Teams of Robots
ROAM: Riemannian Optimization for Active Mapping with Robot Teams
Optimization of Robotic Cells
ARMO - Adaptive Road Map Optimization for Large Robot Teams
Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration
Optimization Based Controller Design and Implementation for the Atlas Robot in the DRC Finals
Optimizing Exploration in Deep Reinforcement Learning for Robotic Control Tasks
View Detailed Profile
Optimization-Based Robot Team Exploration Considering Attrition and Communication Constraints

Optimization-Based Robot Team Exploration Considering Attrition and Communication Constraints

An overview of our 2021 IROS paper (https://ieeexplore.ieee.org/abstract/document/9636029), finding the optimal locations to ...

RangedIK: An Optimization-based Robot Motion Generation Method for Ranged-Goal Tasks

RangedIK: An Optimization-based Robot Motion Generation Method for Ranged-Goal Tasks

Supplementary video of our work: RangedIK: An

Optimization-based Robot Path Planning using Quadratic Programming

Optimization-based Robot Path Planning using Quadratic Programming

A path planner using operator inputs to generate a feasible path. The simulation is conducted using ROS Rviz.

Multi-robot Exploration with Custom RRT* and homotopy classes trajectory optimization integration

Multi-robot Exploration with Custom RRT* and homotopy classes trajectory optimization integration

Hi, I was working with my Multi-

Field Exploration Robots with ACO algorithm - ACO Robots - Maker Faire Rome 2020

Field Exploration Robots with ACO algorithm - ACO Robots - Maker Faire Rome 2020

Robotics

Path Planning with Multiple Rapidly-exploring Random Trees for Teams of Robots

Path Planning with Multiple Rapidly-exploring Random Trees for Teams of Robots

This video addresses the problem of real-time planning and control of a

ROAM: Riemannian Optimization for Active Mapping with Robot Teams

ROAM: Riemannian Optimization for Active Mapping with Robot Teams

Autonomous

Optimization of Robotic Cells

Optimization of Robotic Cells

The video demonstrates our algorithms for

ARMO - Adaptive Road Map Optimization for Large Robot Teams

ARMO - Adaptive Road Map Optimization for Large Robot Teams

More information can be found in the following publications: D. Sun, Alexander Kleiner and C. Schindelhauer. 2010.

Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration

Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration

Mobile

Optimization Based Controller Design and Implementation for the Atlas Robot in the DRC Finals

Optimization Based Controller Design and Implementation for the Atlas Robot in the DRC Finals

Siyuan Feng, X Xinjilefu, Christopher G. Atkeson and Joohyung Kim.

Optimizing Exploration in Deep Reinforcement Learning for Robotic Control Tasks

Optimizing Exploration in Deep Reinforcement Learning for Robotic Control Tasks

IROS DEMO.

Reconnaissance and Exploration with a autonomous Multi Robot Team

Reconnaissance and Exploration with a autonomous Multi Robot Team

Reconnaissance and Exploration with a autonomous Multi Robot Team