Zobrazeno 1 - 10
of 149
pro vyhledávání: '"Pinciroli, Carlo"'
Autor:
Chin, Khai Yi, Pinciroli, Carlo
Collective perception is a fundamental problem in swarm robotics, often cast as best-of-$n$ decision-making. Past studies involve robots with perfect sensing or with small numbers of faulty robots. We previously addressed these limitations by proposi
Externí odkaz:
http://arxiv.org/abs/2410.21546
Autor:
Huang, Chao, Zang, Wenshuo, Pinciroli, Carlo, Li, Zhi Jane, Banerjee, Taposh, Su, Lili, Liu, Rui
Compared with single robots, Multi-Robot Systems (MRS) can perform missions more efficiently due to the presence of multiple members with diverse capabilities. However, deploying an MRS in wide real-world environments is still challenging due to unce
Externí odkaz:
http://arxiv.org/abs/2409.16577
Deep reinforcement learning (DRL) has seen remarkable success in the control of single robots. However, applying DRL to robot swarms presents significant challenges. A critical challenge is non-stationarity, which occurs when two or more robots updat
Externí odkaz:
http://arxiv.org/abs/2306.12926
Autor:
Aswale, Ashay, Pinciroli, Carlo
We present an approach to task scheduling in heterogeneous multi-robot systems. In our setting, the tasks to complete require diverse skills. We assume that each robot is multi-skilled, i.e., each robot offers a subset of the possible skills. This ma
Externí odkaz:
http://arxiv.org/abs/2306.11936
Collective perception is a foundational problem in swarm robotics, in which the swarm must reach consensus on a coherent representation of the environment. An important variant of collective perception casts it as a best-of-$n$ decision-making proces
Externí odkaz:
http://arxiv.org/abs/2209.12858
Autor:
Powers, Stephen, Pinciroli, Carlo
Collective behaviors are typically hard to model. The scale of the swarm, the large number of interactions, and the richness and complexity of the behaviors are factors that make it difficult to distill a collective behavior into simple symbolic expr
Externí odkaz:
http://arxiv.org/abs/2205.00614
The aim of this paper is to study how to apply deep reinforcement learning for the control of aggregates of minimalistic robots. We define aggregates as groups of robots with a physical connection that compels them to form a specified shape. In our c
Externí odkaz:
http://arxiv.org/abs/2203.15129
Autor:
Looney, Tyler C., Savard, Nathan M., Teran, Gus T., Milligan, Archie G., Wheelock, Ryley I., Scalise, Michael, Perno, Daniel P., Lewin, Gregory C., Pinciroli, Carlo, Onal, Cagdas D., Nemitz, Markus P.
The demining of landmines using drones is challenging; air-releasable payloads are typically non-intelligent (e.g., water balloons or explosives) and deploying them at even low altitudes (~6 meter) is inherently inaccurate due to complex deployment t
Externí odkaz:
http://arxiv.org/abs/2202.03243
Ants have evolved to seek and retrieve food by leaving trails of pheromones. This mechanism has inspired several approaches to decentralized multi-robot coordination. However, in this paper, we show that pheromone trails are a fragile mechanism for c
Externí odkaz:
http://arxiv.org/abs/2202.01808
In this paper, we investigate how to design an effective interface for remote multi-human multi-robot interaction. While significant research exists on interfaces for individual human operators, little research exists for the multi-human case. Yet, t
Externí odkaz:
http://arxiv.org/abs/2102.02351