revanth krishna senthilkumaran

revanth senthilkumaran

M.S. Robotics, Carnegie Mellon University
Robot Learning Intern, Bosch Center for AI

I build robot learning systems that reason about physical interaction and transfer manipulation skills across embodiments, tasks, and environments.

research

My goal is to develop general-purpose manipulation policies that combine perception, reasoning, and action—and can reuse knowledge across different robot bodies rather than learning every skill from scratch.

currently

At CMU and the Bosch Center for AI, I study embodied reasoning and cross-embodiment robot learning with Prof. Ding Zhao and Dr. Jonathan Francis. I am especially interested in how demonstrations, video, and interaction data can help robots acquire manipulation skills that generalize.

questions I want to explore

  • How can a robot reason about objects, contacts, and task constraints before it acts?
  • How can demonstrations and human video provide scalable supervision for manipulation?
  • What representations let a learned skill transfer across embodiments and environments?

Background: Before CMU, I earned a B.S. in Computer Engineering from Purdue, worked as a Robotics Software Engineer at AeroVironment, and conducted research at Purdue's SMART Lab with Prof. Byung-Cheol Min, IDEAS Lab with Prof. Aniket Bera, and the Air Force Research Laboratory with Prof. James Goppert. Outside research, I play basketball and piano and enjoy finding new food spots.

latest updates

[JUN 2026] Humanoid Touch Dream accepted to IEEE-IROS 2026

[AUG 2025] Started M.S. in Robotics at Carnegie Mellon University

[JUN 2024] MOCAS dataset accepted to IEEE-TAFFC 2024

[APR 2024] Presented ARTEMIS at Purdue Spring Undergraduate Research Expo and won 2nd place in College of Science Category

[JUN 2023] UPPLIED accepted to IEEE-IROS 2023

selected research

Humanoid Touch Dream Paper

Humanoid Touch Dream: Learning Versatile Humanoid Manipulation with Touch Dreaming

Authors: Yaru Niu, Zhenlong Fang, Binghong Chen, Shuai Zhou, Revanth K. Senthilkumaran, Hao Zhang, Bingqing Chen, Chen Qiu, H. Eric Tseng, Jonathan Francis, Ding Zhao

Status: IEEE-IROS 2026, RSS WCBM Workshop 2026 (ORAL), RSS SemRob Workshop 2026, RSS Tactile for FM Workshop 2026

ARTEMIS Paper

ARTEMIS: AI-Driven Robotic Triage Labeling and Emergency Information System

Authors: Revanth K. Senthilkumaran, Mridu Prashanth, Hrishikesh Viswanath, Sathvika Kotha, Kshitij Tiwari, Aniket Bera

Status: Preprint 2024

UPPLIED Paper

UPPLIED: UAV Path Planning for Learning from Demonstration

Authors: Shyam Sundar Kannan*, Vishnunandan L. N. Venkatesh*, Revanth K. Senthilkumaran, Byung-Cheol Min

* Equal Contribution

Status: IEEE-IROS 2023

MOCAS Paper

MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks

Authors: Wonse Jo*, Ruiqi Wang*, Su Sun, Revanth K. Senthilkumaran, Daniel Foti, Byung-Cheol Min

* Equal Contribution

Status: IEEE-TAFFC 2024

SMARTmBOT Paper

SMARTmBOT: A ROS2-based Low-cost and Open-source Mobile Robot Platform

Authors: Wonse Jo, Jaeeun Kim, Ruiqi Wang, Jeremy Pan, Revanth K. Senthilkumaran, Byung-Cheol Min

Status: Preprint 2022

presentations & talks

Data Collection for Mobile Manipulators

Data Collection for Mobile Manipulators for Learning from Demonstration

Venue: University of Minnesota Summer URC 2023

VF-PLUME

VF-PLUME: Vertical Farming Plant Localizing UAV with Mass Estimation

Venue: Purdue Spring URC 2023

Dynamic Cognitive Workload Allocation

A Dynamic Cognitive Workload Allocation Method for Human Robot Interaction

Venue: Purdue Fall URC 2022

GUI for Measuring Cognitive Workload

A GUI for Measuring Cognitive Workload Stimulus in Human Robot Interaction

Venue: Purdue Spring URC 2022