Robotics Ph.D. student at Carnegie Mellon!

Joined July 2019
Spot dressed up for Halloween!🎃 It's on a mission for its favorite 'candy'! 🔋 But two 'ghosts' were blocking the path… A fun demo of our new paper on how robots can intelligently 'make way' on cluttered stairs! (1/4) @CMU_Robotics
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Do we still need Uncertainty Quantification for robotics? What does uncertainty mean in the modern robotics paradigm? 💡 We are organizing a workshop “Rethinking Uncertainty for Modern Robotics Paradigms” @ IROS 2026 Submit your work by Aug 23! 👇 (rethinking-uncertainty.githu…)
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Organized by: Prasanna Sriganesh (CMU), @Junwon__Seo (CMU), Juyeop Han (MIT), Rosario Scalise (UW), Xiaoyi (Jeremy) Cai (Waymo), Zhiting (May) Mei (Princeton), Sertac Karaman (MIT), @andrea_bajcsy (CMU) | Matthew Travers (CMU)
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🔗 Website & CFP: rethinking-uncertainty.githu… Submission Deadline: August 23, 2026 (AoE) Workshop Date: Sept 27, 2026 Location: Pittsburgh, PA
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A planner then computes safe trajectories, which are executed by a learned pedipulation policy. This tight coupling results in much higher success rates and lets the robot reclassify heavy 'immovable' objects. Here's a look at more technical results: (3/4)
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See all the videos and details on our new project page: ➡️ prassi.me/clearing-clutter-o… Full paper: 📷 arxiv.org/abs/2509.20516 (4/4) #Robotics #Halloween2025 #AI
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The code for our work on staircase perception is now public. This repository includes implementations from our papers on Bayesian staircase estimation and fast staircase detection. Code: github.com/Prassi07/staircas…
Making robots safer on stairs! 💪 Our new work, just accepted to RA-L, introduces a clever way for robots to perceive the whole staircase, even when parts are hidden from view! 👀 Full paper: ieeexplore.ieee.org/document… @CMU_Robotics (1/4)
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Bayesian Inference: We use this model with Bayesian inference to intelligently combine noisy sensor readings with prior knowledge about staircase already seen. This combination lets us tackle challenges like occlusions, clutter, limited field-of-view and sensor noise. (3/4)
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But that's not all! We also use this information to segment the stair surfaces and remove clutter, enabling safer navigation on staircases. 🤖 Check out our project website for more info and images! 👉 prassi.me/bayesian-staircase… (4/4)
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Making robots safer on stairs! 💪 Our new work, just accepted to RA-L, introduces a clever way for robots to perceive the whole staircase, even when parts are hidden from view! 👀 Full paper: ieeexplore.ieee.org/document… @CMU_Robotics (1/4)
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How does this work? We've developed a method that combines two techniques: Staircase Modeling: We create a model that parameterizes and represents the state of the entire staircase, including parts the robot can't currently see. (2/4)
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Prasanna Sriganesh retweeted
Hello all, We are excited to organize the first workshop on Learning for Soft Robots at #CoRL2023! Through our amazing line-up of speakers, we hope to motivate future research in various soft robotic areas such as manipulation, locomotion, sensors, and embodied perception!
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On the Friday of July 28th, I successfully finished my masters thesis on a staircase perception system for mobile robots. Also, I'll be continuing as a Ph.D student at @CMU_Robotics this fall.
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We finally have a social media presence. Follow to know more about our cool robots and the new work that's happening here!
Hi everyone! We are the CMU Biorobotics Lab and we are on Twitter to spread awareness of the work we do at the lab. From modular and autonomous robots to our famous snake robot, we have many unique projects and breakthrough research we are excited to share!
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If you're curious and want to see a few robots we have at the Mattlab in The Robotics Institute, here's a video. youtu.be/aS8Z8RiCsXQ This was covered by @NEXTpittsburgh #Robotics #cmu
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