Zobrazeno 1 - 10
of 1 794
pro vyhledávání: '"Bell, A I"'
Autor:
Das, Goutam, Rostobaya, Violetta, Berneburg, James, Bell, Zachary I., Dorothy, Michael, Shishika, Daigo
In this paper, we consider a target defense game in which the attacker team seeks to reach a high-value target while the defender team seeks to prevent that by capturing them away from the target. To address the curse of dimensionality, a popular app
Externí odkaz:
http://arxiv.org/abs/2409.09302
Publikováno v:
2024 IEEE Conference on Control Technology and Applications (CCTA)
This research is motivated by a scenario where a group of UAVs is assigned to map an unknown scalar field, with the imperative of maintaining a safe distance from the sources of the field to evade detection or damage. The location of the sources is u
Externí odkaz:
http://arxiv.org/abs/2407.13543
In this paper, a novel online, output-feedback, critic-only, model-based reinforcement learning framework is developed for safety-critical control systems operating in complex environments. The developed framework ensures system stability and safety,
Externí odkaz:
http://arxiv.org/abs/2406.18804
This letter presents a novel guidance law for target tracking applications where the target motion model is unknown and sensor measurements are intermittent due to unknown environmental conditions and low measurement update rate. In this work, the ta
Externí odkaz:
http://arxiv.org/abs/2402.00671
Autor:
Ogri, Tochukwu Elijah, Qureshi, Muzaffar, Bell, Zachary I., Waters, Kristy, Kamalapurkar, Rushikesh
This paper presents an integral concurrent learning (ICL)-based observer for a monocular camera to accurately estimate the Euclidean distance to features on a stationary object, under the restriction that state information is unavailable. Using dista
Externí odkaz:
http://arxiv.org/abs/2401.09658
In this article, we present an algorithm that drives the outputs of a network of agents to jointly track the solutions of time-varying optimization problems in a way that is robust to asynchrony in the agents' operations. We consider three operations
Externí odkaz:
http://arxiv.org/abs/2312.00646
This paper studies a target-defense game played between a slow defender and a fast attacker. The attacker wins the game if it reaches the target while avoiding the defender's capture disk. The defender wins the game by preventing the attacker from re
Externí odkaz:
http://arxiv.org/abs/2311.03338
Autor:
Lamb, Zachary, Bell, Zachary I., Longmire, Matthew, Paquet, Jared, Ganesh, Prashant, Sanfelice, Ricardo
Recent literature in the field of machine learning (ML) control has shown promising theoretical results for a Deep Neural Network (DNN) based Nonlinear Adaptive Controller (DNAC) capable of achieving trajectory tracking for nonlinear systems. Expandi
Externí odkaz:
http://arxiv.org/abs/2310.09502
Autor:
Riess, Hans, Henselman-Petrusek, Gregory, Munger, Michael C., Ghrist, Robert, Bell, Zachary I., Zavlanos, Michael M.
Preferences, fundamental in all forms of strategic behavior and collective decision-making, in their raw form, are an abstract ordering on a set of alternatives. Agents, we assume, revise their preferences as they gain more information about other ag
Externí odkaz:
http://arxiv.org/abs/2310.00179
Real-world control applications in complex and uncertain environments require adaptability to handle model uncertainties and robustness against disturbances. This paper presents an online, output-feedback, critic-only, model-based reinforcement learn
Externí odkaz:
http://arxiv.org/abs/2304.01526