The Resilient Intelligent Systems Lab (RISLab) is part of Carnegie Mellon University’s Robotics Institute. The lab, led by Co-Directors Wennie Tabib and Nathan Michael, is focused on improving the performance and reliability of autonomous systems.
News
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July 04, 2023
RISLab organizing R:SS 2023 Workshop on Gaussian mixture models for inference and robot autonomy
RISLab will be organizing a tutorial titled “Gaussian Mixture Models for Inference and Robot Autonomy” on July 14, 2023. The code, tutorials, and paper have been released. We hope to see you at the workshop in Daegu, ROK!
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June 22, 2023
Kshitij's paper accepted for presentation at IROS 2023!
Kshitij will be presenting “Probabilistic Point Cloud Modeling via Self-Organizing Gaussian Mixture Models” at IROS 2023 in Detroit, MI.
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June 01, 2023
Honorable Mention for IEEE T-RO King-Sun Fu Memorial Best Paper Award
RISLab received an honorable mention for the IEEE T-RO King-Sun Fu Memorial Best Paper Award. This award is for our work “Autonomous Cave Surveying with an Aerial Robot”, which presents an exploration method in darkness using an aerial robot equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights.
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Active Research Projects
Collaborative Human-Robot Exploration via Implicit Coordination
This research seeks to enable human-robot collaborative exploration of a-priori unknown enviornments using implicit coordination.
Scalable and Adaptive Aerial Robotic Exploration
This research project develops mapping and planning methods for multirotors to enable memory-efficient exploration while generating a high-fidelity map of the environment.
Assistive Adaptive-Speed Multirotor Teleoperation
This research project seeks to improve assistance to humans operating multirotors through narrow gaps and tunnels.
Autonomous Cave Surveying
This research program develops a method for cave surveying in complete darkness with an autonomous aerial vehicle equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights.
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