Zobrazeno 1 - 10
of 226
pro vyhledávání: '"Shah, Naman"'
Autor:
Dobhal, Daksh, Nagpal, Jayesh, Karia, Rushang, Verma, Pulkit, Nayyar, Rashmeet Kaur, Shah, Naman, Srivastava, Siddharth
Understanding how robots plan and execute tasks is crucial in today's world, where they are becoming more prevalent in our daily lives. However, teaching non-experts the complexities of robot planning can be challenging. This work presents an open-so
Externí odkaz:
http://arxiv.org/abs/2404.00808
Hand-crafted, logic-based state and action representations have been widely used to overcome the intractable computational complexity of long-horizon robot planning problems, including task and motion planning problems. However, creating such represe
Externí odkaz:
http://arxiv.org/abs/2402.11871
Autor:
Shah, Naman, Srivastava, Siddharth
This paper addresses the problem of reliably and efficiently solving broad classes of long-horizon stochastic path planning problems. Starting with a vanilla RL formulation with a stochastic dynamics simulator and an occupancy matrix of the environme
Externí odkaz:
http://arxiv.org/abs/2210.00068
Autor:
Shah, Naman, Srivastava, Siddharth
This paper addresses the problem of learning abstractions that boost robot planning performance while providing strong guarantees of reliability. Although state-of-the-art hierarchical robot planning algorithms allow robots to efficiently compute lon
Externí odkaz:
http://arxiv.org/abs/2202.00907
This paper presents JEDAI, an AI system designed for outreach and educational efforts aimed at non-AI experts. JEDAI features a novel synthesis of research ideas from integrated task and motion planning and explainable AI. JEDAI helps users create hi
Externí odkaz:
http://arxiv.org/abs/2111.00585
Autor:
Shah, Naman, Srivastava, Siddharth
In order to solve complex, long-horizon tasks, intelligent robots need to carry out high-level, abstract planning and reasoning in conjunction with motion planning. However, abstract models are typically lossy and plans or policies computed using the
Externí odkaz:
http://arxiv.org/abs/2108.12537
Robot motion planning involves computing a sequence of valid robot configurations that take the robot from its initial state to a goal state. Solving a motion planning problem optimally using analytical methods is proven to be PSPACE-Hard. Sampling-b
Externí odkaz:
http://arxiv.org/abs/2012.00658
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Shah, Naman, Vasudevan, Deepak Kala, Kumar, Kislay, Kamojjhala, Pranav, Srivastava, Siddharth
In order to solve complex, long-horizon tasks, intelligent robots need to carry out high-level, abstract planning and reasoning in conjunction with motion planning. However, abstract models are typically lossy and plans or policies computed using the
Externí odkaz:
http://arxiv.org/abs/1904.13006
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.