Gautam Salhotra

Gautam Salhotra

Robotics & AI Research

I am robotics reseacher at Intrinsic, working with Stefan Schaal. Previously, I completed my PhD in computer science (robotics) at the University of Southern California (USC), advised by Gaurav Sukhatme. My thesis was on learning visuomotor manipulation skills for robotic arms, using the methods of learning from demonstration (LfD) and Reinforcement Learning (RL). I have applied this primarily to dexterous manipulation such as cloth manipulation and precision assembly tasks. More broadly, I have worked on combining planning algorithms with learning to achieve greater autonomy for robots, with experience in object manipulation, control theory, and learning.

Download my résumé (2 page) and CV (full).

Interests
  • Dexterous Robot Manipulation
  • Deformable Objects
  • Learning from Demonstrations
  • Reinforcement Learning
Education
  • PhD in Computer Science (Robotics), 2024

    University of Southern California

News

Selected Publications

See Google Scholar for a full list

(2023). Learning Robot Manipulation from Cross-Morphology Demonstration. In CoRL 2023.

Cite Website PDF Code

(2022). Learning Deformable Object Manipulation from Expert Demonstrations. In IEEE RA-L, IROS ‘22.

Cite Website PDF Code

(2022). Guided Learning of Robust Hurdling Policies with Curricular Trajectory Optimization. In SoCal Robotics Symposium ‘22.

PDF Cite Website

(2021). Adaptive Sampling using POMDPs with Domain-Specific Considerations. In ICRA ‘21.

Cite Code

(2020). Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. In CoRL ‘20.

Cite Website PDF Code