Nakul Gopalan
Nakul Gopalan
Post Doctoral fellow Georgia Tech
Verified email at - Homepage
Cited by
Cited by
Bayesian gait optimization for bipedal locomotion
R Calandra, N Gopalan, A Seyfarth, J Peters, MP Deisenroth
International conference on learning and intelligent optimization, 274-290, 2014
Accurately and efficiently interpreting human-robot instructions of varying granularities
D Arumugam, S Karamcheti, N Gopalan, LLS Wong, S Tellex
arXiv preprint arXiv:1704.06616, 2017
Robots that use language
S Tellex, N Gopalan, H Kress-Gazit, C Matuszek
Annual Review of Control, Robotics, and Autonomous Systems 3, 25-55, 2020
Learning to parse natural language to grounded reward functions with weak supervision
EC Williams, N Gopalan, M Rhee, S Tellex
2018 IEEE International Conference on Robotics and Automation (ICRA), 4430-4436, 2018
Planning with abstract Markov decision processes
N Gopalan, ML Littman, J MacGlashan, S Squire, S Tellex, J Winder, ...
Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017
Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications.
N Gopalan, D Arumugam, LLS Wong, S Tellex
Robotics: Science and Systems, 2018
Modeling and solving human-robot collaborative tasks using pomdps
N Gopalan, S Tellex
RSS Workshop on Model Learning for Human-Robot Communication 32 (4), 590-628, 2015
Flight, camera, action! using natural language and mixed reality to control a drone
B Huang, D Bayazit, D Ullman, N Gopalan, S Tellex
2019 International Conference on Robotics and Automation (ICRA), 6949-6956, 2019
A tale of two draggns: A hybrid approach for interpreting action-oriented and goal-oriented instructions
S Karamcheti, EC Williams, D Arumugam, M Rhee, N Gopalan, LLS Wong, ...
arXiv preprint arXiv:1707.08668, 2017
Grounding natural language instructions to semantic goal representations for abstraction and generalization
D Arumugam, S Karamcheti, N Gopalan, EC Williams, M Rhee, LLS Wong, ...
Autonomous Robots 43 (2), 449-468, 2019
Grounding language attributes to objects using bayesian eigenobjects
V Cohen, B Burchfiel, T Nguyen, N Gopalan, S Tellex, G Konidaris
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
Feedback error learning for rhythmic motor primitives
N Gopalan, MP Deisenroth, J Peters
2013 IEEE International Conference on Robotics and Automation, 1317-1322, 2013
Robot Object Retrieval with Contextual Natural Language Queries
T Nguyen, N Gopalan, R Patel, M Corsaro, E Pavlick, S Tellex
arXiv preprint arXiv:2006.13253, 2020
Simultaneously learning transferable symbols and language groundings from perceptual data for instruction following
N Gopalan, E Rosen, GD Konidaris, S Tellex
Robotics: Science and Systems XVI, 2020
Mitigating planner overfitting in model-based reinforcement learning
D Arumugam, D Abel, K Asadi, N Gopalan, C Grimm, JK Lee, L Lehnert, ...
arXiv preprint arXiv:1812.01129, 2018
Interpretable Policy Specification and Synthesis through Natural Language and RL
P Tambwekar, A Silva, N Gopalan, M Gombolay
arXiv preprint arXiv:2101.07140, 2021
An Approach to Human-Robot Collaborative Drilling and Fastening in Aerospace Final Assembly
M Johnson, R Liu, N Gopalan, M Gombolay
AIAA Scitech 2021 Forum, 0270, 2021
Interpreting human-robot instructions
S Tellex, D Arumugam, S Karamcheti, N Gopalan, LLS Wong
US Patent 10,606,898, 2020
Social feedback for robotic collaboration
E Wu, N Gopalan, J MacGlashan, S Tellex, LL Wong
Interpreting human-robot instructions
S Tellex, D Arumugam, S Karamcheti, N Gopalan, LLS Wong
US Patent App. 16/806,706, 2020
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