Zobrazeno 1 - 10
of 124
pro vyhledávání: '"Siami, Milad"'
We introduce a novel dataset for multi-robot activity recognition (MRAR) using two robotic arms integrating WiFi channel state information (CSI), video, and audio data. This multimodal dataset utilizes signals of opportunity, leveraging existing WiFi
Externí odkaz:
http://arxiv.org/abs/2408.16703
Motivated by the growing use of Artificial Intelligence (AI) tools in control design, this paper takes the first steps towards bridging the gap between results from Direct Gradient methods for the Linear Quadratic Regulator (LQR), and neural networks
Externí odkaz:
http://arxiv.org/abs/2408.15456
Vision-based methods are commonly used in robotic arm activity recognition. These approaches typically rely on line-of-sight (LoS) and raise privacy concerns, particularly in smart home applications. Passive Wi-Fi sensing represents a new paradigm fo
Externí odkaz:
http://arxiv.org/abs/2407.06154
This paper introduces a novel method for the stability analysis of positive feedback systems with a class of fully connected feedforward neural networks (FFNN) controllers. By establishing sector bounds for fully connected FFNNs without biases, we pr
Externí odkaz:
http://arxiv.org/abs/2406.12744
Numerical ``direct'' approaches to time-optimal control often fail to find solutions that are singular in the sense of the Pontryagin Maximum Principle, performing better when searching for saturated (bang-bang) solutions. In previous work by one of
Externí odkaz:
http://arxiv.org/abs/2406.07644
Autor:
Wafi, Moh. Kamalul, Siami, Milad
This paper addresses the challenge of network synchronization under limited communication, involving heterogeneous agents with different dynamics and various network topologies, to achieve consensus. We investigate the distributed adaptive control fo
Externí odkaz:
http://arxiv.org/abs/2405.15178
Despite the current surge of interest in autonomous robotic systems, robot activity recognition within restricted indoor environments remains a formidable challenge. Conventional methods for detecting and recognizing robotic arms' activities often re
Externí odkaz:
http://arxiv.org/abs/2312.15345
Autonomous robotic systems have gained a lot of attention, in recent years. However, accurate prediction of robot motion in indoor environments with limited visibility is challenging. While vision-based and light detection and ranging (LiDAR) sensors
Externí odkaz:
http://arxiv.org/abs/2307.03829
Recent research in neural networks and machine learning suggests that using many more parameters than strictly required by the initial complexity of a regression problem can result in more accurate or faster-converging models -- contrary to classical
Externí odkaz:
http://arxiv.org/abs/2305.09904
