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The design space for a self-assembled multicomponent objects ranges from a solution in which every building block is unique to one with the minimum number of distinct building blocks that unambiguously define the target structure. Using a…

Soft Condensed Matter · Physics 2023-03-13 Joakim Bohlin , Andrew J. Turberfield , Ard A. Louis , Petr Šulc

Image-guided object assembly represents a burgeoning research topic in computer vision. This paper introduces a novel task: translating multi-view images of a structural 3D model (for example, one constructed with building blocks drawn from…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Hongyu Yan , Yadong Mu

The physical design of a robot and the policy that controls its motion are inherently coupled, and should be determined according to the task and environment. In an increasing number of applications, data-driven and learning-based…

Robotics · Computer Science 2018-09-18 Charles Schaff , David Yunis , Ayan Chakrabarti , Matthew R. Walter

When autonomous agents interact in the same environment, they must often cooperate to achieve their goals. One way for agents to cooperate effectively is to form a team, make a binding agreement on a joint plan, and execute it. However,…

Automatic assembly has broad applications in industries. Traditional assembly tasks utilize predefined trajectories or tuned force control parameters, which make the automatic assembly time-consuming, difficult to generalize, and not robust…

Artificial Intelligence · Computer Science 2019-04-17 Yongxiang Fan , Jieliang Luo , Masayoshi Tomizuka

Manipulation and assembly tasks require non-trivial planning of actions depending on the environment and the final goal. Previous work in this domain often assembles particular instances of objects from known sets of primitives. In…

Robotics · Computer Science 2020-10-02 Alexander Pashevich , Igor Kalevatykh , Ivan Laptev , Cordelia Schmid

While reinforcement learning has achieved considerable successes in recent years, state-of-the-art models are often still limited by the size of state and action spaces. Model-free reinforcement learning approaches use some form of state…

Machine Learning · Computer Science 2021-08-23 Paul J. Pritz , Liang Ma , Kin K. Leung

Autonomous robots require high degrees of cognitive and motoric intelligence to come into our everyday life. In non-structured environments and in the presence of uncertainties, such degrees of intelligence are not easy to obtain.…

Most successes in autonomous robotic assembly have been restricted to single target or category. We propose to investigate general part assembly, the task of creating novel target assemblies with unseen part shapes. As a fundamental step to…

Robotics · Computer Science 2023-09-06 Yulong Li , Andy Zeng , Shuran Song

Object rearrangement is a fundamental problem in robotics with various practical applications ranging from managing warehouses to cleaning and organizing home kitchens. While existing research has primarily focused on single-agent…

Robotics · Computer Science 2023-11-07 Vivek Gupta , Praphpreet Dhir , Jeegn Dani , Ahmed H. Qureshi

Understanding physical phenomena is a key competence that enables humans and animals to act and interact under uncertain perception in previously unseen environments containing novel objects and their configurations. In this work, we…

Robotics · Computer Science 2019-04-23 Wenbin Li , Aleš Leonardis , Jeannette Bohg , Mario Fritz

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

Assembling a slave object into a fixture-free master object represents a critical challenge in flexible manufacturing. Existing deep reinforcement learning-based methods, while benefiting from visual or operational priors, often struggle…

Robotics · Computer Science 2024-06-04 Chuang Wang , Lie Yang , Ze Lin , Yizhi Liao , Gang Chen , Longhan Xie

In this work we propose a novel task framework under which a variety of physical reasoning puzzles can be constructed using very simple rules. Under sparse reward settings, most of these tasks can be very challenging for a reinforcement…

Artificial Intelligence · Computer Science 2018-12-04 Yixiu Zhao , Ziyin Liu

In this paper, we present a machine learning approach to move a group of robots in a formation. We model the problem as a multi-agent reinforcement learning problem. Our aim is to design a control policy for maintaining a desired formation…

Robotics · Computer Science 2020-01-15 Abhay Rawat , Kamalakar Karlapalem

This paper proposes an assembly sequence planning framework, named Subassembly to Assembly (S2A). The framework is designed to enable a robotic manipulator to assemble multiple parts in a prespecified structure by leveraging object…

Robotics · Computer Science 2024-09-23 Chang Shu , Anton Kim , Shinkyu Park

Multi-part assembly poses significant challenges for robots to execute long-horizon, contact-rich manipulation with generalization across complex geometries. We present Fabrica, a dual-arm robotic system capable of end-to-end planning and…

Autonomous assembly has been a desired functionality of many intelligent robot systems. We study a new challenging assembly task, designing and constructing a bridge without a blueprint. In this task, the robot needs to first design a…

Robotics · Computer Science 2021-08-06 Yunfei Li , Tao Kong , Lei Li , Yifeng Li , Yi Wu

It is desirable to enable robots capable of automatic assembly. Structural understanding of object parts plays a crucial role in this task yet remains relatively unexplored. In this paper, we focus on the setting of furniture assembly from…

Robotics · Computer Science 2022-07-07 Rufeng Zhang , Tao Kong , Weihao Wang , Xuan Han , Mingyu You

Many tasks in control, robotics, and planning can be specified using desired goal configurations for various entities in the environment. Learning goal-conditioned policies is a natural paradigm to solve such tasks. However, current…

Machine Learning · Computer Science 2022-03-14 Allan Zhou , Vikash Kumar , Chelsea Finn , Aravind Rajeswaran