Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Parasuraman, Ramviyas"'
Robot systems in education can leverage Large language models' (LLMs) natural language understanding capabilities to provide assistance and facilitate learning. This paper proposes a multimodal interactive robot (PhysicsAssistant) built on YOLOv8 obj
Externí odkaz:
http://arxiv.org/abs/2403.18721
Autor:
Li, Yiwei, Wu, Zihao, Zhao, Huaqin, Yang, Tianze, Liu, Zhengliang, Shu, Peng, Sun, Jin, Parasuraman, Ramviyas, Liu, Tianming
To tackle the "reality gap" encountered in Sim-to-Real transfer, this study proposes a diffusion-based framework that minimizes inconsistencies in grasping actions between the simulation settings and realistic environments. The process begins by trai
Externí odkaz:
http://arxiv.org/abs/2403.11459
Multi-agent and multi-robot systems (MRS) often rely on direct communication for information sharing. This work explores an alternative approach inspired by eavesdropping mechanisms in nature that involves casual observation of agent interactions to
Externí odkaz:
http://arxiv.org/abs/2312.11802
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
We propose integrating the edge-computing paradigm into the multi-robot collaborative scheduling to maximize resource utilization for complex collaborative tasks, which many robots must perform together. Examples include collaborative map-merging to
Externí odkaz:
http://arxiv.org/abs/2311.10194
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
To circumvent persistent connectivity to the cloud infrastructure, the current emphasis on computing at network edge devices in the multi-robot domain is a promising enabler for delay-sensitive jobs, yet its adoption is rife with challenges. This pap
Externí odkaz:
http://arxiv.org/abs/2311.10196
Urban vehicle-to-vehicle (V2V) link scheduling with shared spectrum is a challenging problem. Its main goal is to find the scheduling policy that can maximize system performance (usually the sum capacity of each link or their energy efficiency). Give
Externí odkaz:
http://arxiv.org/abs/2310.08364
Autor:
Latif, Ehsan, Parasuraman, Ramviyas
Relative localization is crucial for multi-robot systems to perform cooperative tasks, especially in GPS-denied environments. Current techniques for multi-robot relative localization rely on expensive or short-range sensors such as cameras and LIDARs
Externí odkaz:
http://arxiv.org/abs/2307.10614
Autor:
Latif, Ehsan, Parasuraman, Ramviyas
Localizing mobile robotic nodes in indoor and GPS-denied environments is a complex problem, particularly in dynamic, unstructured scenarios where traditional cameras and LIDAR-based sensing and localization modalities may fail. Alternatively, wireles
Externí odkaz:
http://arxiv.org/abs/2307.01956
CQLite: Communication-Efficient Multi-Robot Exploration Using Coverage-biased Distributed Q-Learning
Autor:
Latif, Ehsan, Parasuraman, Ramviyas
Frontier exploration and reinforcement learning have historically been used to solve the problem of enabling many mobile robots to autonomously and cooperatively explore complex surroundings. These methods need to keep an internal global map for navi
Externí odkaz:
http://arxiv.org/abs/2307.00500
Autor:
Latif, Ehsan, Parasuraman, Ramviyas
The availability of accurate localization is critical for multi-robot exploration strategies; noisy or inconsistent localization causes failure in meeting exploration objectives. We aim to achieve high localization accuracy with contemporary explorat
Externí odkaz:
http://arxiv.org/abs/2306.12623