RISLab: Home

The Resilient Intelligent Systems Lab (RISLab) is part of Carnegie Mellon University’s Robotics Institute. The lab, led by PI Wennie Tabib, improves the performance and reliability of autonomous systems.

News

December 06, 2024

Kshitij Goel Defends PhD Thesis!
Congratulations to Kshitij Goel for a successful PhD thesis defense! Well done! His thesis focuses on communication-efficient active multi-robot reconstruction using self-organizing Gaussian mixture models. The thesis document is available here. A video recording of the defense talk is available on YouTube.
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November 14, 2024

RISLab and NREC Win Best Paper Award at SSRR 2024
New York, November 14 – Researchers from the Resilient Intelligent Systems Lab (RISLab) at the Robotics Institute (RI) and the National Robotics and Engineering Center (NREC) have received the Best Paper Award at the IEEE Symposium on Safety, Security, and Rescue Robotics (SSRR) 2024 for their work titled Rapid Quadrotor Navigation in Diverse Environments using an Onboard Depth Camera. This award recognizes outstanding contributions to field robotics, particularly in advancing safety, security, and rescue operations through innovative navigation technology for multirotor vehicles.
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April 30, 2024

Wennie Presents RISL Research to Members of Congress
Wennie presented RISL research to members of Congress and their staff at the “Robotics for a Better Tomorrow: Robotics Showcase and Demo Day” in Washington, D.C. on April 30.
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Active Research Projects

Rapid Navigation in Diverse Environments

This research innovates techniques for rapid navigation in forests, caves, and other cluttered, unstructured environments.

Large-Scale Decentralized Multirobot Active Search

This research project leverages reinforcement learning to enable decentralized multirobot active search over large scales.

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.