Zobrazeno 1 - 10
of 980
pro vyhledávání: '"Deshpande, A. M."'
Central Pattern Generators (CPGs) form the neural basis of the observed rhythmic behaviors for locomotion in legged animals. The CPG dynamics organized into networks allow the emergence of complex locomotor behaviors. In this work, we take this inspi
Externí odkaz:
http://arxiv.org/abs/2302.13191
Deep reinforcement learning (RL) has made it possible to solve complex robotics problems using neural networks as function approximators. However, the policies trained on stationary environments suffer in terms of generalization when transferred from
Externí odkaz:
http://arxiv.org/abs/2111.03915
Autor:
Mamidi, Nischay Ram, Prasun, Kumar, Saxena, Dhruv, Nemili, Anil, Sharma, Bharatkumar, Deshpande, S. M.
This report presents a comprehensive analysis of the performance of GPU accelerated meshfree CFD solvers for two-dimensional compressible flows in Fortran, C++, Python, and Julia. The programming model CUDA is used to develop the GPU codes. The meshf
Externí odkaz:
http://arxiv.org/abs/2108.07031
The temperature distribution in the battery significantly impacts the short-term and long-term performance of battery systems. Therefore, efficient, safe, and reliable battery system operation requires an accurate estimation of the temperature field.
Externí odkaz:
http://arxiv.org/abs/2105.05976
Publikováno v:
In Thin-Walled Structures February 2024 195
In this paper the tracking problem of multi-agent systems, in a particular scenario where a segment of agents entering a sensing-denied environment or behaving as non-cooperative targets, is considered. The focus is on determining the optimal sensor
Externí odkaz:
http://arxiv.org/abs/2103.00739
We consider the problem of sensor selection for designing observer and filter for continuous linear time invariant systems such that the sensor precisions are minimized, and the estimation errors are bounded by the prescribed $\mathcal{H}_2/\mathcal{
Externí odkaz:
http://arxiv.org/abs/2103.00750
We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty. The problem is formulated in the $\mathcal{H}_{\infty}$ op
Externí odkaz:
http://arxiv.org/abs/2009.01930
In this paper, we present a novel developmental reinforcement learning-based controller for a quadcopter with thrust vectoring capabilities. This multirotor UAV design has tilt-enabled rotors. It utilizes the rotor force magnitude and direction to ac
Externí odkaz:
http://arxiv.org/abs/2007.07793
Autor:
Kumar, Rumit, Bhargavapuri, Mahathi, Deshpande, Aditya M., Sridhar, Siddharth, Cohen, Kelly, Kumar, Manish
In this paper, we present an autonomous flight controller for a quadcopter with thrust vectoring capabilities. This UAV falls in the category of multirotors with tilt-motion enabled rotors. Since the vehicle considered is over-actuated in nature, the
Externí odkaz:
http://arxiv.org/abs/2006.15686