Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Paleja, Rohan"'
Optimization for robot control tasks, spanning various methodologies, includes Model Predictive Control (MPC). However, the complexity of the system, such as non-convex and non-differentiable cost functions and prolonged planning horizons often drast
Externí odkaz:
http://arxiv.org/abs/2408.03394
As learned control policies become increasingly common in autonomous systems, there is increasing need to ensure that they are interpretable and can be checked by human stakeholders. Formal specifications have been proposed as ways to produce human-i
Externí odkaz:
http://arxiv.org/abs/2407.02632
Collaborative robots and machine learning-based virtual agents are increasingly entering the human workspace with the aim of increasing productivity and enhancing safety. Despite this, we show in a ubiquitous experimental domain, Overcooked-AI, that
Externí odkaz:
http://arxiv.org/abs/2406.05003
The emergence of Large Language Models (LLMs) has revealed a growing need for human-AI collaboration, especially in creative decision-making scenarios where trust and reliance are paramount. Through human studies and model evaluations on the open-end
Externí odkaz:
http://arxiv.org/abs/2406.02018
Autor:
Paleja, Rohan, Chen, Letian, Niu, Yaru, Silva, Andrew, Li, Zhaoxin, Zhang, Songan, Ritchie, Chace, Choi, Sugju, Chang, Kimberlee Chestnut, Tseng, Hongtei Eric, Wang, Yan, Nageshrao, Subramanya, Gombolay, Matthew
Interpretability in machine learning is critical for the safe deployment of learned policies across legally-regulated and safety-critical domains. While gradient-based approaches in reinforcement learning have achieved tremendous success in learning
Externí odkaz:
http://arxiv.org/abs/2311.10041
We study a search and tracking (S&T) problem where a team of dynamic search agents must collaborate to track an adversarial, evasive agent. The heterogeneous search team may only have access to a limited number of past adversary trajectories within a
Externí odkaz:
http://arxiv.org/abs/2306.11301
The need for opponent modeling and tracking arises in several real-world scenarios, such as professional sports, video game design, and drug-trafficking interdiction. In this work, we present Graph based Adversarial Modeling with Mutal Information (G
Externí odkaz:
http://arxiv.org/abs/2306.11168
Autor:
Lee, Kin Man, Krishna, Arjun, Zaidi, Zulfiqar, Paleja, Rohan, Chen, Letian, Hedlund-Botti, Erin, Schrum, Mariah, Gombolay, Matthew
Publikováno v:
HRI '23: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
As high-speed, agile robots become more commonplace, these robots will have the potential to better aid and collaborate with humans. However, due to the increased agility and functionality of these robots, close collaboration with humans can create s
Externí odkaz:
http://arxiv.org/abs/2304.03756
Autor:
Krishna, Arjun, Zaidi, Zulfiqar, Chen, Letian, Paleja, Rohan, Seraj, Esmaeil, Gombolay, Matthew
Agile robotics presents a difficult challenge with robots moving at high speeds requiring precise and low-latency sensing and control. Creating agile motion that accomplishes the task at hand while being safe to execute is a key requirement for agile
Externí odkaz:
http://arxiv.org/abs/2212.14403
Autor:
Zaidi, Zulfiqar, Martin, Daniel, Belles, Nathaniel, Zakharov, Viacheslav, Krishna, Arjun, Lee, Kin Man, Wagstaff, Peter, Naik, Sumedh, Sklar, Matthew, Choi, Sugju, Kakehi, Yoshiki, Patil, Ruturaj, Mallemadugula, Divya, Pesce, Florian, Wilson, Peter, Hom, Wendell, Diamond, Matan, Zhao, Bryan, Moorman, Nina, Paleja, Rohan, Chen, Letian, Seraj, Esmaeil, Gombolay, Matthew
Athletics are a quintessential and universal expression of humanity. From French monks who in the 12th century invented jeu de paume, the precursor to modern lawn tennis, back to the K'iche' people who played the Maya Ballgame as a form of religious
Externí odkaz:
http://arxiv.org/abs/2210.02517