G
Gautam Salhotra
Researcher at University of Southern California
Publications - 19
Citations - 95
Gautam Salhotra is an academic researcher from University of Southern California. The author has contributed to research in topics: Computer science & Reinforcement learning. The author has an hindex of 5, co-authored 13 publications receiving 41 citations. Previous affiliations of Gautam Salhotra include Indian Institute of Technology Bombay.
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Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
Jun Yamada,Youngwoon Lee,Gautam Salhotra,Karl Pertsch,Max Pflueger,Gaurav S. Sukhatme,Joseph J. Lim,Peter Englert +7 more
TL;DR: MoPA-RL as mentioned in this paper augments the action space of an RL agent with the long-horizon planning capabilities of motion planners, which leads to faster exploration and safer policies that avoid collisions with the environment.
Posted Content
PLGRIM: Hierarchical Value Learning for Large-scale Exploration in Unknown Environments
Sung-Kyun Kim,Amanda Bouman,Gautam Salhotra,David D. Fan,Kyohei Otsu,Joel W. Burdick,Ali-akbar Agha-mohammadi +6 more
TL;DR: In this article, a scalable value learning framework, PLGRIM (Probabilistic Local and Global Reasoning on Information roadmaps), is proposed to bridge the gap between (i) local, risk-aware resiliency and (ii) global, reward-seeking mission objectives.
Posted Content
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge.
Ali Agha,Kyohei Otsu,Benjamin Morrell,David D. Fan,Rohan Thakker,Angel Santamaria-Navarro,Sung-Kyun Kim,Amanda Bouman,Xianmei Lei,Jeffrey A. Edlund,Muhammad Fadhil Ginting,Kamak Ebadi,Matthew Anderson,Torkom Pailevanian,Edward Terry,Michael Wolf,Andrea Tagliabue,Tiago Stegun Vaquero,Matteo Palieri,Scott Tepsuporn,Yun Chang,Arash Kalantari,Fernando Chavez,Brett T. Lopez,Nobuhiro Funabiki,Gregory Miles,Thomas Touma,Alessandro Buscicchio,Jesus Tordesillas,Nikhilesh Alatur,Jeremy Nash,William Walsh,Sunggoo Jung,Hanseob Lee,Christoforos Kanellakis,John Mayo,Scott Harper,Marcel Kaufmann,Anushri Dixit,Gustavo J. Correa,Carlyn Lee,Jay Gao,Gene Merewether,Jairo Maldonado-Contreras,Gautam Salhotra,Maira Saboia da Silva,Benjamin Ramtoula,Yuki Kubo,Seyed Abolfazl Fakoorian,Alexander Hatteland,Taeyeon Kim,Tara Bartlett,Alex Stephens,Leon Kim,Chuck Bergh,Eric Heiden,Thomas Lew,Abhishek Cauligi,Tristan Heywood,Andrew Kramer,Henry A. Leopold,Hyungho Chris Choi,Shreyansh Daftry,Olivier Toupet,Inhwan Wee,Abhishek Thakur,Micah Feras,Giovanni Beltrame,George Nikolakopoulos,David Hyunchul Shim,Luca Carlone,Joel W. Burdick +71 more
TL;DR: NeBula as mentioned in this paper is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states).
Journal ArticleDOI
Learning Deformable Object Manipulation From Expert Demonstrations
TL;DR: A novel Learning from Demonstration method to solve deformable manipulation tasks using states or images as inputs, given expert demonstrations, and balances the trade-off between exploring the environment online and using guidance from experts to explore high dimensional spaces effectively.
Journal ArticleDOI
NeBula: TEAM CoSTAR’s Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge
Ali Agha,Kyohei Otsu,Benjamin Morrell,David D. Fan,Rohan Thakker,Àngel Santamaria Navarro,Sung-Hyun Kim,Amanda Bouman,Xianmei Lei,Jeffrey A. Edlund,Muhammad Fadhil Ginting,Kamak Ebadi,Matthew O. Anderson,Torkom Pailevanian,Edward Prentice Terry,Michael Wolf,and Lorenzo Tagliabue,Tiago Stegun Vaquero,Matteo Palieri,Scott Tepsuporn,Yun Chang,Arash Kalantari,Fernando Chavez,Brett T. Lopez,Nobuhiro Funabiki,Gregory Miles,Thomas Touma,Alessandro Buscicchio,Jesus Tordesillas,Nikhilesh Alatur,Jeremy Nash,William Walsh,Sun-Hwi Jung,Han Eol Lee,Christoforos Kanellakis,John Mayo,Scott Harper,Marcel Kaufmann,Anushri Dixit,Gustavo J. Correa,Carlyn-Ann Lee,Jay L. Gao,Gene Merewether,Jairo Maldonado-Contreras,Gautam Salhotra,Maira Saboia Da Silva,Benjamin Ramtoula,Seyed Abolfazl Fakoorian,Alex Hatteland,Taeyeon Kim,Tara Bartlett,Alex Stephens,Leon Kim,Charles F. Bergh,Eric Heiden,Thomas Lew,Abhishek Cauligi,Tristan Heywood,Andrew Kramer,H. Leopold,Hovhannes Melikyan,Hyung-Yong Choi,Shreyansh Daftry,Olivier Toupet,Inhwan Wee,Abhishek Thakur,Micah Feras,Giovanni Alberto Beltrame,George Nikolakopoulos,Da-Yeon Shim,Luca Carlone,Joel W. Burdick +71 more
TL;DR: The paper introduces the autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy), an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states).