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Combinatorial assembly uses standardized unit primitives to build objects that satisfy user specifications. This paper studies assembly sequence planning (ASP) for physical combinatorial assembly. Given the shape of the desired object, the…

Robotics · Computer Science 2025-03-25 Ruixuan Liu , Alan Chen , Weiye Zhao , Changliu Liu

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based planning approach for…

Automatic Robotic Assembly Sequence Planning (RASP) can significantly improve productivity and resilience in modern manufacturing along with the growing need for greater product customization. One of the main challenges in realizing such…

Robotics · Computer Science 2023-07-28 Matan Atad , Jianxiang Feng , Ismael Rodríguez , Maximilian Durner , Rudolph Triebel

This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Production Line Planning (PLP), employing a graph-based approach to model components and joints…

Assembly planning is a difficult problem for companies. Many disciplines such as design, planning, scheduling, and manufacturing execution need to be carefully engineered and coordinated to create successful product assembly plans. Recent…

Robotics · Computer Science 2020-05-13 Jade Master , Evan Patterson , Shahin Yousfi , Arquimedes Canedo

Automating the assembly of objects from their parts is a complex problem with innumerable applications in manufacturing, maintenance, and recycling. Unlike existing research, which is limited to target segmentation, pose regression, or…

Robotics · Computer Science 2023-12-19 Xinghao Zhu , Devesh K. Jha , Diego Romeres , Lingfeng Sun , Masayoshi Tomizuka , Anoop Cherian

Inferring step-wise actions to assemble 3D objects with primitive bricks from images is a challenging task due to complex constraints and the vast number of possible combinations. Recent studies have demonstrated promising results on…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Mengqi Guo , Chen Li , Yuyang Zhao , Gim Hee Lee

Answer set programming (ASP) is a popular nonmonotonic-logic based paradigm for knowledge representation and solving combinatorial problems. Computing the answer set of an ASP program is NP-hard in general, and researchers have been…

Logic in Computer Science · Computer Science 2021-09-21 Fang Li

This paper proposes a robot assembly planning method by automatically reading the graphical instruction manuals design for humans. Essentially, the method generates an Assembly Task Sequence Graph (ATSG) by recognizing a graphical…

Answer set programming (ASP) is a popular nonmonotonic-logic based paradigm for knowledge representation and solving combinatorial problems. Computing the answer set of an ASP program is NP-hard in general, and researchers have been…

Artificial Intelligence · Computer Science 2021-04-06 Fang Li , Huaduo Wang , Gopal Gupta

This paper develops a planner to find an optimal assembly sequence to assemble several objects. The input to the planner is the mesh models of the objects, the relative poses between the objects in the assembly, and the final pose of the…

Robotics · Computer Science 2016-09-13 Weiwei Wan , Kensuke Harada , Kazuyuki Nagata

Answer Set Programming (ASP) is a well-known problem-solving formalism in computational logic. Nowadays, ASP is used in many real world scenarios thanks to ASP solvers. Standard evaluation of ASP programs suffers from an intrinsic…

Logic in Computer Science · Computer Science 2021-09-20 Giuseppe Mazzotta

We propose a synthetic reasoning task, LEGO (Learning Equality and Group Operations), that encapsulates the problem of following a chain of reasoning, and we study how the Transformer architectures learn this task. We pay special attention…

Machine Learning · Computer Science 2023-02-21 Yi Zhang , Arturs Backurs , Sébastien Bubeck , Ronen Eldan , Suriya Gunasekar , Tal Wagner

The optimal robot assembly planning problem is challenging due to the necessity of finding the optimal solution amongst an exponentially vast number of possible plans, all while satisfying a selection of constraints. Traditionally, robotic…

Robotics · Computer Science 2025-02-25 Kartik Nagpal , Negar Mehr

The sequence in which a complex product is assembled directly impacts the ease and efficiency of the assembly process, whether executed by a human or a robot. A sequence that gives the assembler the greatest freedom of movement is therefore…

Robotics · Computer Science 2019-07-10 James Watson , Tucker Hermans

Autonomous assembly of objects is an essential task in robotics and 3D computer vision. It has been studied extensively in robotics as a problem of motion planning, actuator control and obstacle avoidance. However, the task of developing a…

Computer Vision and Pattern Recognition · Computer Science 2021-08-02 Abhinav Narayan Harish , Rajendra Nagar , Shanmuganathan Raman

Detecting small sets of relevant patterns from a given dataset is a central challenge in data mining. The relevance of a pattern is based on user-provided criteria; typically, all patterns that satisfy certain criteria are considered…

Artificial Intelligence · Computer Science 2020-02-19 Sergey Paramonov , Daria Stepanova , Pauli Miettinen

This article presents the use of Answer Set Programming (ASP) to mine sequential patterns. ASP is a high-level declarative logic programming paradigm for high level encoding combinatorial and optimization problem solving as well as…

Artificial Intelligence · Computer Science 2017-11-15 Thomas Guyet , Yves Moinard , René Quiniou , Torsten Schaub

Autonomous agents powered by large language models (LLMs) have shown impressive capabilities in tool manipulation for complex task-solving. However, existing paradigms such as ReAct rely on sequential reasoning and execution, failing to…

Artificial Intelligence · Computer Science 2025-10-30 Jiaqi Wu , Qinlao Zhao , Zefeng Chen , Kai Qin , Yifei Zhao , Xueqian Wang , Yuhang Yao

Graph Neural Networks (GNN) have been shown to work effectively for modeling graph structured data to solve tasks such as node classification, link prediction and graph classification. There has been some recent progress in defining the…

Machine Learning · Computer Science 2020-02-04 Ekagra Ranjan , Soumya Sanyal , Partha Pratim Talukdar
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