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In this paper, we propose SwarmNet -- a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network…

Neural and Evolutionary Computing · Computer Science 2020-11-04 Siyu Zhou , Mariano Phielipp , Jorge A. Sefair , Sara I. Walker , Heni Ben Amor

In this paper, we study the problem of manipulation skill acquisition for performing construction activities consisting of repetitive tasks (e.g., building a wall or installing ceiling tiles). Our approach involves setting up a simulated…

Robotics · Computer Science 2026-05-14 Wangyi Liu , Dasharadhan Mahalingam , Fanru Gao , Ci-Jyun Liang , Nilanjan Chakraborty

Learning from demonstration is widely used as an efficient way for robots to acquire new skills. However, it typically requires that demonstrations provide full access to the state and action sequences. In contrast, learning from…

Machine Learning · Computer Science 2020-08-05 Zachary W. Robertson , Matthew R. Walter

We find that across a wide range of robot policy learning scenarios, treating supervised policy learning with an implicit model generally performs better, on average, than commonly used explicit models. We present extensive experiments on…

An important factor in developing control models for human-robot collaboration is how acceptable they are to their human partners. One such method for creating acceptable control models is to attempt to mimic human-like behaviour in robots…

Robotics · Computer Science 2022-07-12 Rebeka Kropivšek Leskovar , Tadej Petrič

This paper reports a case study on the User Experience (UX)of an industrial robotic prototype in the context of human-robot cooperation in an automotive assembly line. The goal was to find out what kinds of suggestions the assembly line…

Robotics · Computer Science 2016-06-14 Astrid Weiss , Andreas Huber

Robotic assembly is a longstanding challenge, requiring contact-rich interaction and high precision and accuracy. Many applications also require adaptivity to diverse parts, poses, and environments, as well as low cycle times. In other…

Significant progress in robotics reveals new opportunities to advance manufacturing. Next-generation industrial automation will require both integration of distinct robotic technologies and their application to challenging industrial…

Wire-harnessing tasks pose great challenges to be automated by the robot due to the complex dynamics and unpredictable behavior of the deformable wire. Traditional methods, often reliant on dual-robot arms or tactile sensing, face…

Robotics · Computer Science 2024-10-15 Xiang Zhang , Hsien-Chung Lin , Yu Zhao , Masayoshi Tomizuka

The design of physical compliance -- its location, degree, and structure -- affects robot performance and robustness in contact-rich tasks. While compliance is often used in the robot's joints, flange, or end-effector, this paper proposes…

Robotics · Computer Science 2022-03-15 Richard Hartisch , Kevin Haninger

Complicated assembly processes can be described as a sequence of two main activities: grasping and insertion. While general grasping solutions are common in industry, insertion is still only applicable to small subsets of problems, mainly…

Robotics · Computer Science 2021-04-30 Oren Spector , Dotan Di Castro

Contact-rich manipulation tasks with stiff frictional elements like connector insertion are difficult to model with rigid-body simulators. In this work, we propose a new approach for modeling these environments by learning a quasi-static…

Robotics · Computer Science 2023-12-15 Kevin Tracy , Zachary Manchester , Ajinkya Jain , Keegan Go , Stefan Schaal , Tom Erez , Yuval Tassa

Humans possess an extraordinary ability to understand and execute complex manipulation tasks by interpreting abstract instruction manuals. For robots, however, this capability remains a substantial challenge, as they cannot interpret…

Manipulation tasks often consist of subtasks, each representing a distinct skill. Mastering these skills is essential for robots, as it enhances their autonomy, efficiency, adaptability, and ability to work in their environment. Learning…

Robotics · Computer Science 2025-05-21 Juyan Zhang , Dana Kulic , Michael Burke

Accurate robot kinematics is essential for precise tool placement in articulated robots, but non-geometric factors can introduce configuration-dependent model discrepancies. This paper presents a configuration-dependent kinematic…

Robotics · Computer Science 2025-10-24 Chen-Lung Lu , Honglu He , Agung Julius , John T. Wen

This work aims to interpret human behavior to anticipate potential user confusion when a robot provides explanations for failure, allowing the robot to adapt its explanations for more natural and efficient collaboration. Using a dataset…

Robotics · Computer Science 2025-04-15 Andreas Naoum , Parag Khanna , Elmira Yadollahi , Mårten Björkman , Christian Smith

Advanced building control methods such as model predictive control (MPC) offer significant potential benefits to both consumers and grid operators, but the high computational requirements have acted as barriers to more widespread adoption.…

Systems and Control · Electrical Eng. & Systems 2021-04-02 Zachary E. Lee , K. Max Zhang

Human-robot cooperation is essential in environments such as warehouses and retail stores, where workers frequently handle deformable objects like paper, bags, and fabrics. Coordinating robotic actions with human assistance remains…

Robotics · Computer Science 2025-11-06 Rewida Ali , Cristian C. Beltran-Hernandez , Weiwei Wan , Kensuke Harada

Fine robotic assembly, in which the parts to be assembled are small and fragile and lie in an unstructured environment, is still out of reach of today's industrial robots. The main difficulties arise in the precise localization of the parts…

Robotics · Computer Science 2015-09-17 Francisco Suárez-Ruiz , Quang-Cuong Pham

Learning control policies for visual servoing in novel environments is an important problem. However, standard model-free policy learning methods are slow. This paper explores planner cloning: using behavior cloning to learn policies that…

Robotics · Computer Science 2020-05-26 Ulrich Viereck , Kate Saenko , Robert Platt
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