Reliable Autonomous Systems Lab at MIT (REALM)

Reliable Autonomous Systems Lab (REALM) @MIT.
We design, analyze and verify safe control systems.

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Our code is open source!

Code: https://t.co/h85OKkETRW

Arxiv: https://t.co/WVqStePOqI
Web: https://t.co/ZUGKu0DTFY
Video: https://t.co/Ue9sh6owW8

🧵 (7/7)

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Excited to present two works at #CoRL2023, both at Poster Session 6 on Thursday 4:15 pm!

🧵 (1/7)

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

By predicting a diverse set of possible failures prior to deployment, we can make sure robots of all sizes (from drones to power grids) stay safe.

🧵 (6/7)

[MIT School of Engineering @MITEngineering]

An @MITAeroAstro team developed a machine-learning technique that can autonomously fly a plane through a difficult “stabilize-avoid” scenario while avoiding obstacles.

Read more at MIT News https://t.co/9xouNpnWC0

[KUNAL GARG @kunalgarg94]

Great @l4dc_conf talk by @mit_REALM PhD student Songyuan Zhang

[KUNAL GARG @kunalgarg94]

@mit_REALM dinner after @l4dc_conf day 1

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Come to the poster sessions and oral presentations! Yue’s work will appear in Poster Session 1 while Songyuan’s will appear in Poster Session 2. Songyuan will provide a deeper introduction to his work on Friday at the “Oral Presentations 4” time slot. See you there! (2/2)

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

REALM has two strong works being presented at @l4dc_conf this year. @YueMengTHU 's “Hybrid Systems Neural Control with Region-of-Attraction Planner” and Songyuan Zhang’s “Compositional Neural Certificates for Networked Dynamical Systems” will be presented! To learn more... (1/2)

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Please attend @l4dc_conf, if you're interested in hearing from Yue first-hand!

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

A huge number robotics problems can be modeled as hybrid dynamical systems, and these are known to be difficult to define controllers for. In @YueMengTHU ‘s new work (accepted to L4DC), we have developed a method for designing controllers for this important class of systems!

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

And further information can be found here: https://t.co/Rzy3ZVEKzq

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

enough soft robot simulator. (3/3)

https://t.co/j8nYv6X0UI

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Sound interesting? Then, play around with his implementation of this work which is located in REALM’s Architect repository: https://t.co/r84ItRXLDJ

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

An exciting question that came from a vigorous discussion at REALM last week:

What differentiable simulators exist that can model soft robotic systems interacting withe the world?

(1/3)
#AcademicChatter #RoboticsChatter #DifferentiableSimulation

[Reliable Autonomous Systems Lab at MIT (REALM) @mit_REALM]

Context: REALM has established its passion for differentiable simulation in several different results (see our work on Architect) and we were having a spirited discussion last week about how better sensor placement/design might be possible if we had a good (2/3)