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Simulation frameworks such as Isaac Sim have enabled scalable robot learning for locomotion and rigid-body manipulation; however, contact-rich simulation remains a major bottleneck for deformable object manipulation. The continuously…

Industrial robots are widely used in manufacturing, yet most manipulation still depends on fixed waypoint scripts that are brittle to environmental changes. Learning-based control offers a more adaptive alternative, but it remains unclear…

Robotics · Computer Science 2026-04-27 Yunho Kim , Quan Nguyen , Taewhan Kim , Youngjin Heo , Joonho Lee

Utilizing robotic systems in the construction industry is gaining popularity due to their build time, precision, and efficiency. In this paper, we introduce a system that allows the coordination of multiple manipulator robots for…

Robotics · Computer Science 2024-05-28 Mohammad Reza Kolani , Stavros Nousias , André Borrmann

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

Deformable object manipulation is a classical and challenging research area in robotics. Compared with rigid object manipulation, this problem is more complex due to the deformation properties including elastic, plastic, and elastoplastic…

Contact-rich tasks pose significant challenges for robotic systems due to inherent uncertainty, complex dynamics, and the high risk of damage during interaction. Recent advances in learning-based control have shown great potential in…

Robotics · Computer Science 2026-01-27 Heng Zhang , Rui Dai , Gokhan Solak , Pokuang Zhou , Yu She , Arash Ajoudani

Physics-based simulation is essential for developing and evaluating robot manipulation policies, particularly in scenarios involving deformable objects and complex contact interactions. However, existing simulators often struggle to balance…

We introduce a robotic assembly system that streamlines the design-to-make workflow for going from a CAD model of a product assembly to a fully programmed and adaptive assembly process. Our system captures (in the CAD tool) the intent of…

Robotics · Computer Science 2022-08-04 Yotto Koga , Heather Kerrick , Sachin Chitta

Most of industrial robotic assembly tasks today require fixed initial conditions for successful assembly. These constraints induce high production costs and low adaptability to new tasks. In this work we aim towards flexible and adaptable…

Robotics · Computer Science 2019-03-26 Yuval Litvak , Armin Biess , Aharon Bar-Hillel

Learning from demonstration is one of the most promising methods to counteract the challenging long-term trends in repetitive industrial assembly. It offers not only a programming technique that is accessible to workers on the shop floor,…

Robotics · Computer Science 2023-10-03 V. Hernandez Moreno , S. Jansing , M. Polikarpov , M. G. Carmichael , J. Deuse

Building a deployable PhysiComp that merges form and function typically involves a significant investment of time and skill in digital electronics, 3D modeling and mechanical design. We aim to help designers quickly create prototypes by…

Human-Computer Interaction · Computer Science 2017-09-19 Michael Jones , Kevin Seppi

Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback. However, it is non-trivial to manually design a robot controller that combines modalities with very different characteristics. While…

As robots become increasingly prominent in diverse industrial settings, the desire for an accessible and reliable system has correspondingly increased. Yet, the task of meaningfully assessing the feasibility of introducing a new robotic…

Robotics · Computer Science 2023-05-26 Minh Q. Tram , Joseph M. Cloud , William J. Beksi

Simulation-based learning has enabled policies for precise, contact-rich tasks (e.g., robotic assembly) to reach high success rates (~80%) under high levels of observation noise and control error. Although such performance may be sufficient…

Previous methods for Learning from Demonstration leverage several approaches for a human to teach motions to a robot, including teleoperation, kinesthetic teaching, and natural demonstrations. However, little previous work has explored more…

Robotics · Computer Science 2025-03-14 Michael Hagenow , Dimosthenis Kontogiorgos , Yanwei Wang , Julie Shah

Granular materials are of critical interest to many robotic tasks in planetary science, construction, and manufacturing. However, the dynamics of granular materials are complex and often computationally very expensive to simulate. We…

Robotics · Computer Science 2023-06-05 David Millard , Daniel Pastor , Joseph Bowkett , Paul Backes , Gaurav S. Sukhatme

This paper presents a simulation-driven approach for automating the force-controlled assembly of electrical terminals on DIN-rails, a task traditionally hindered by high programming effort and product variability. The proposed method…

Contact-rich manipulation tasks often exhibit a large sim-to-real gap. For instance, industrial assembly tasks frequently involve tight insertions where the clearance is less than 0.1 mm and can even be negative when dealing with a…

Robotics · Computer Science 2024-03-04 Xiang Zhang , Masayoshi Tomizuka , Hui Li

Collaborative robots are expected to be able to work alongside humans and in some cases directly replace existing human workers, thus effectively responding to rapid assembly line changes. Current methods for programming contact-rich tasks,…

As collaborative robots (cobots) continue to gain popularity in industrial manufacturing, effective human-robot collaboration becomes crucial. Cobots should be able to recognize human actions to assist with assembly tasks and act…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Dustin Aganian , Mona Köhler , Benedict Stephan , Markus Eisenbach , Horst-Michael Gross