Robotic Space Exploration (RoSE) Lab at Colorado School of Mines
The RoSE Lab at Colorado School of Mines advances methods for mobile autonomous robots in extreme space environments including orbital satellites, extraplanetary oceans, and planetary surfaces. Research integrates dynamics, control theory, and machine learning for autonomous exploration in scientifically-rich extreme settings.
Notable achievements
Algorithms for lunar and Martian rover navigation, underwater extraplanetary exploration
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
A fusion prediction model of tool wear based on physical information and machine learning in five-axis milling TC4 titanium alloy
Shaoqing Qin, Lida Zhu, Yanpeng Hao +7 more
Robotics and Computer-Integrated Manufacturing · 2026
Design and dynamic performance prediction of a novel large-aperture offset-feed deployable antenna
Chuang Shi, Tianming Liu, Ning Xue +6 more
Aerospace Science and Technology · 2026
A machine learning–based tool for enhancing position accuracy in industrial robots with a reduced dataset
Giuseppe Romano, Pietro Bilancia, Alberto Locatelli +3 more
Robotics and Computer-Integrated Manufacturing · 2026
Generalized machine learning model for deformation prediction and compensation in robotic machining
Taehwa Hong, Gyuho Kim, Seong Hyeon Kim +1 more
Robotics and Computer-Integrated Manufacturing · 2026
Wheeled autonomous rover design and control for snow-covered terrain
Austin P. Lines, Adam Gronewold, Joshua Elliot +6 more
Robotics and Autonomous Systems · 2026
Performance Comparison of Classical and Neural Sampling Algorithms for Robotic Navigation
Hichem Cheriet, Badra Khellat Kihel, Samira Chouraqui
2026