Febrianto Eko Sucahyo, Wahyu Dirgantara, Resi Dewi Jayanti Kartika Sari

Prototype Palang Pintu Perlintasan Kereta Api Otomatis Menggunakan Komunikasi LoRa RFM95

Robotics

Railway crossing doors are railway facilities or infrastructure to protect train travel and provide warnings to road users. This prototype automatic r...

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Risky Odang Sanjaya, Novian Fajar Satria, Himmawan Sabda Maulana

Pemodelan dan simulasi kinematika robot SCARA 3 derajat kebebasan menggunakan MATLAB

Robotics

Zaman yang serba canggih di semua aspek kehidupan sudah menggunakan bantuan teknologi. Seperti contoh dalam hal produksi barang di dalam industri yang...

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This paper, "Pemodelan dan simulasi kinematika robot SCARA 3 derajat kebebasan menggunakan MATLAB," addresses a pertinent topic in robotics: the kinem...

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Hendi Purnata, Hera Susanti, Dwi Sahidin, Galih Mustiko Aji, Nanda Pranandita

Adaptive PID–PD Hybrid Control for Precise Motion of ROVs in Dynamic Environments

Robotics

This study aims to develop and evaluate an Adaptive PID–PD Hybrid Control System to enhance the position and rotation control of a Remotel...

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This study presents an investigation into an Adaptive PID–PD Hybrid Control System designed to improve the precision of Remotely Operated Vehicles (RO...

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Yimin Tang, Xiao Xiong, Jingyi Xi, Jiaoyang Li, Erdem Bıyık, Sven Koenig

RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks (Extended Abstract)

Robotics

Multi-Agent Path Finding (MAPF), which focuses on finding collision-free paths for multiple robots, is crucial for applications ranging from aerial sw...

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This extended abstract introduces RAILGUN, a novel learning-based policy designed to address the Multi-Agent Path Finding (MAPF) problem. The authors...

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Kareem Eissa, Rayal Prasad, Ankur Kapoor

Multi-Agent Path Finding for Schedule Constrained Automation (Extended Abstract)

Robotics

In modern automation settings, jobs are processed across machines with interdependencies and are subject to limited equipment availability. When trans...

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The paper "Multi-Agent Path Finding for Schedule Constrained Automation" introduces MAPF-SC, an extension of Multi-Agent Path Finding (MAPF) designed...

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Jonathan Morag, Noy Gabay, Daniel Koyfman, Roni Stern

Should Multi-Agent Path Finding Algorithms Coordinate Target Arrival Times?

Robotics

Multi-Agent Path Finding (MAPF) deals with finding conflict-free paths for a set of agents from an initial configuration to a given target configurati...

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This position paper critically examines a fundamental inefficiency in current approaches to Lifelong Multi-Agent Path Finding (LMAPF), specifically th...

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Runzhe Liang, Rishi Veerapaneni, Daniel Harabor, Jiaoyang Li, Maxim Likhachev

Real-Time LaCAM for Real-Time MAPF

Robotics

The vast majority of Multi-Agent Path Finding (MAPF) methods with completeness guarantees require planning full-horizon paths. However, planning full-...

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This paper addresses a significant challenge in Multi-Agent Path Finding (MAPF): the practical limitations of full-horizon planning in real-world, tim...

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Matan Sudry, Tom Jurgenson, Erez Karpas

Task and Motion Planning Using Infinite Completion Tree and Agnostic Skills

Robotics

This work builds upon existing task and motion planning (TAMP) frameworks by integrating pre-trained Sequencing Task-Agnostic Policies (STAP) and Effo...

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This paper presents a compelling advancement in Task and Motion Planning (TAMP) by introducing a hierarchical framework designed to tackle long-horizo...

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Yaakov Sherma, Eyal Weiss, Oren Salzman

From Agent Centric to Obstacle Centric Planning: A Makespan-Optimal Algorithm for the Multi-Agent Warehouse Rearrangement Problem

Robotics

The Multi-Agent Warehouse Rearrangement (MAWR) problem calls for computing agents plans such that they collectively rearrange a warehouse environment...

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This paper tackles the Multi-Agent Warehouse Rearrangement (MAWR) problem, a complex and practical variant of Multi-Agent Path Finding (MAPF) and Mult...

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Muhammad Suhail Saleem, Rishi Veerapaneni, Maxim Likhachev

Lazy Heuristic Search for Solving POMDPs with Expensive-to-Compute Belief Transitions

Robotics

Heuristic search solvers like RTDP-Bel and LAO* have proven effective for computing optimal and bounded sub-optimal solutions for Partially Observable...

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This paper addresses a critical practical limitation in solving Partially Observable Markov Decision Processes (POMDPs) using heuristic search methods...

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