Search · four archives
Search · four archives
18 papers · ranked by Valyu relevance
Li, Nan, Ren, Jiming + 8 more
—Multi-Agent Task Assignment and Planning (MATP) has attracted growing attention but remains challenging in terms of scalability, spatial reasoning, and adaptability in obstacle-rich environments. To address these challenges, we propose OATH — Adaptive Obstacle-Aware Task Assignment and Planning for Heterogeneous Robot…
Shi, Guangyao, Wu, Yuwei + 4 more
— Enabling robot teams to execute natural language commands requires translating high-level instructions into feasible, efficient multi-robot plans. While Large Language Models (LLMs) combined with Planning Domain Description Language (PDDL) offer promise for single-robot scenarios, existing approaches struggle with…
Jakob Bichler, Andreu Matoses Gimenez, Javier Alonso-Mora
— We present Sadcher, a real-time task assignment framework for heterogeneous multi-robot teams that incorporates dynamic coalition formation and task precedence constraints. Sadcher is trained through Imitation Learning and combines graph attention and transformers to predict assignment rewards between robots and…
Suraj Borate, Bhavish Rai B, Vipul Pardeshi, Madhu Vadali
Heterogeneous multi-robot teams require systems that can interpret natural-language goals, allocate tasks, and adapt to unexpected events. We developed CoMuRoS (Collaborative Multi-Robot System), a generalizable hierarchical architecture combining a centralized task-manager LLM with decentralized robot-level LLMs for…
Jiazhen Liu, Glen Neville, Jinwoo Park, Sonia Chernova + 1 more
Complex multi-robot missions often require heterogeneous teams to jointly optimize task allocation, scheduling, and path planning to improve team performance under strict constraints. We formalize these complexities into a new class of problems, dubbed Spatio-Temporal Efficacy-optimized Allocation for Multi-robot…
Yichao Wang, Chunjiang Wang, Shuangyin Ren, Leopoldo Angrisani
In multi-UAV cooperative tasks, dynamic communication topologies and resource heterogeneity present significant challenges for distributed task allocation, leading to high communication overhead and poor task-resource matching, which in turn increases computational costs. While the Consensus-Based Bundle Algorithm…
Weifei Gan, Hongxuan Xu, Yunwei Bai, Xin Zhou + 3 more
Large multi-UAV mission systems operate over time-varying communication graphs with heterogeneous platforms, where classical distributed task assignment may incur excessive message passing and suboptimal task-resource matching. To address these challenges, this paper proposes CLAC-CBBA (Centrality-Driven and Load-Aware…
Ding Tianyi, Zheng Ronghao, Zhang Sen-lin, Liu + 1 more
—This work addresses the collaborative multi-robot autonomous online exploration problem, particularly focusing on distributed exploration planning for dynamically balanced exploration area partition and task allocation among a team of mobile robots operating in obstacle-dense non-convex environments. We present a…
Benjamin M. David, Paul A. Jensen
Coordinating multiple liquid handling robots is a complex logistical task when designing biological experiments. Protocol designers must consider the capabilities and constraints of each robot to distribute work optimally across multiple instruments. We developed an optimization framework that finds optimal liquid…
Zhengyang He, Xiaojie Tang, Fengyun Zhang
With the rapid development of robot technology, the multi-robot cooperation system has been widely used in rescue, monitoring, logistics, and other fields. Aiming at the key problems in multi-robot cooperative localization and target search, considering the search time, search mileage, and search risk, a cooperative…
Amir Ijaz, Hashem Haghbayan, Ethiopia Nigussie, Juha Plosila + 2 more
Energy-efficient coordination of robotic swarms requires effective integration of task scheduling, motion planning, and communication management, particularly in resource-constrained environments where computation and wireless communication compete for limited energy resources. Existing multi-robot approaches typically…
Jie Gao, Weinan Xie, Haoya Liu, Junda Zhou + 3 more
Multi-AGV (Automated Guided Vehicle) systems operating in complex warehouse environments equipped with movable containers encounter several challenges, including high system no-load rate, low task response efficiency, and imbalanced path utilization. To address these issues, we propose an integrated optimization…
Tianfu Zhang, Suet Lee, Heiko Hamann
From animal societies to self-organizing multi-agent systems, collectives adapt their group structure to tasks and environments. However, how they determine appropriate group sizes and the number of subgroups to form remains unclear. We formulate the Group Size and Number Regulation Problem (GSNRP), which asks how…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
Process chemistry creates scalable routes for new lead molecules and is a crucial but laborious stage in pharmaceutical and agrochemical development cycles. We have built an automated process chemistry platform that tackles late-stage process development. The modular workflow integrates both industry-standard tools and…
Pol Fernández-López, Jolle W. Jolles, Daniel Oro, Frederic Bartumeus
Task allocation in eusocial insects has long been studied under the framework of division of labor, implying a relatively rigid association between individuals and tasks. However, most eusocial species lack morphological specialization, and workers regularly switch tasks as colony demands change. This raises a…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…