KRIS: A Robot for Material Transport in Relief Situations

This paper presents KRIS, a semi-autonomous robot developed for material transport in disaster relief situations. In collaboration with the German Federal Agency for Technical Relief (THW) and the German Research Center for Artificial Intelligence (DFKI), KRIS addresses the limitations of manual transport in hazardous environments. The robot is designed for enhanced mobility in rough terrain, featuring modes such as manual control, gesture-based person-following, and autonomous shuttle operation. The system is equipped with advanced sensors, including LiDAR and RGB-D cameras, and employs AI-driven gesture recognition for hands-free operation. Two field tests evaluated KRIS's usability in realistic disaster settings, demonstrating its ability to transport heavy equipment while reducing physical strain on rescue personnel. The findings highlight the potential of KRIS to improve efficiency and safety in disaster relief operations.

Authors

Institutions

Publication Details

Published
2024-11-12
DOI
https://doi.org/10.1109/ssrr62954.2024.10770027
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

KRIS: A Robot for Material Transport in Relief Situations

Vamsi Krishna Origanti, Frank Kirchner, Martin Mallwitz, Mehmed Yüksel et al.
Advanced Manufacturing and Logistics Optimization
article

KRIS: A Robot for Material Transport in Relief Situations

Vamsi Krishna Origanti, Frank Kirchner, Martin Mallwitz, Mehmed Yüksel, Felix Bernhard, Thomas Becker, Fabian Maas Genannt Bermpoh, Daniel Weissenrieder, Milan Sixt, Malika Navaratna Helapita Ralalagc, Christian School, Miguel Martínez Genis
article en

Abstract

This paper presents KRIS, a semi-autonomous robot developed for material transport in disaster relief situations. In collaboration with the German Federal Agency for Technical Relief (THW) and the German Research Center for Artificial Intelligence (DFKI), KRIS addresses the limitations of manual transport in hazardous environments. The robot is designed for enhanced mobility in rough terrain, featuring modes such as manual control, gesture-based person-following, and autonomous shuttle operation. The system is equipped with advanced sensors, including LiDAR and RGB-D cameras, and employs AI-driven gesture recognition for hands-free operation. Two field tests evaluated KRIS's usability in realistic disaster settings, demonstrating its ability to transport heavy equipment while reducing physical strain on rescue personnel. The findings highlight the potential of KRIS to improve efficiency and safety in disaster relief operations.

Federal Emergency Management Agency (US), German Research Centre for Artificial Intelligence (DE)
Climate action
Openalex Percentile: Top 68%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

KRIS: A Robot for Material Transport in Relief Situations — Vamsi Krishna Origanti, Frank Kirchner, et al. · (2024) | TGRS Research Map | TGRS