Gautam Salhotra

I am a PhD candidate in computer science (robotics & machine learning) at the University of Southern California (USC), advised by Gaurav Sukhatme. Broadly, I work on combining planning algorithms with learning to achieve greater autonomy for robots, with experience in object manipulation, control theory, and deep reinforcement learning.

Research interests

• Inductive biases in robot learning
• Robot autonomy in manipulation

Recent Updates

• Jun 2022: Our paper on learning deformable object manipulation from expert demonstrations has been accepted to both IEEE RA-L and IEEE IROS 2022. See you in Kyoto! (RA-L link)

• May 2022: I presented our work on learning deformable manipulation from expert demonstrations at the 2nd workshop on deformable object manipulation at ICRA 2022 in Philadelphia. (PDF, video)

• Jan 2022: I have accepted an internship at Amazon Robotics this summer.

• May 2021: Chaired ICRA 2021 session on "Field Robotics: Control".

• Mar 2021: Our paper on adaptive sampling with POMDPs for environmental monitoring has been accepted to ICRA 2021! (PDF)

• Feb 2021: Our paper on planning for large-scale exploration in the real world has been accepted to ICAPS 2021! This is part of an ongoing collaboration with NASA JPL and Caltech for the SubT challenge. (PDF).

• Oct 2020: Our paper on augmenting reinforcement learning algorithms with motion planning has been accepted to CoRL 2020! See you at CoRL! (PDF, website).

Select Publications

See my Google Scholar profile or CV for a full list.

• Gautam Salhotra^*, I-Chun Arthur Liu^*, Marcus Dominguez-Kuhne, Gaurav S. Sukhatme. "Learning Deformable Manipulation from Expert Demonstrations". Journal submission, In IEEE Robotics and Automation Letters and International Conference on Intelligent Robots and Systems (IROS), Oct 2022 (RA-L link).
• Gautam Salhotra^*, Christopher E. Denniston^*, David A. Caron and Gaurav S. Sukhatme. "Adaptive Sampling using POMDPs with Domain-Specific Considerations". In International Conference on Robotics and Automation (ICRA), May 2021. (PDF)
• Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph Lim and Peter Englert. "Motion Planner Augmented Reinforcement Learning for Obstructed Environments". In Conference on Robot Learning (CoRL), Nov 2020. (PDF, Website)
• Sung-Kyun Kim^*, Amanda Bouman^*, Gautam Salhotra, David D. Fan, Kyohei Otsu, Joel Burdick, Ali-akbar Agha-mohammadi. "PLGRIM: Hierarchical Value Learning for Large-scale Exploration in Unknown Environments". ICAPS 2021. (PDF)