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Simulation modeling of robots, objects, and environments is the backbone for all model-based control and learning. It is leveraged broadly across dynamic programming and model-predictive control, as well as data generation for imitation,…

Robotics · Computer Science 2022-01-19 Fei Liu , Mingen Li , Jingpei Lu , Entong Su , Michael C. Yip

Identifying the parameters of robotic systems, such as motor inertia or joint friction, is critical to satisfactory controller synthesis, model analysis, and observer design. Conventional identification techniques are designed primarily for…

Robotics · Computer Science 2024-08-19 Bohao Zhang , Daniel Haugk , Ram Vasudevan

We present the design of a low-cost wheeled mobile robot, and an analytical model for predicting its motion under the influence of motor torques and friction forces. Using our proposed model, we show how to analytically compute the gradient…

Robotics · Computer Science 2020-09-25 Yanshi Luo , Abdeslam Boularias , Mridul Aanjaneya

In the field of robotic manipulation, the proficiency of deformable object manipulation lags behind human capabilities due to the inherent characteristics of deformable objects. These objects have infinite degrees of freedom, resulting in…

Robotics · Computer Science 2023-11-17 Peng Zhou

Controlling the deformation of flexible objects is challenging due to their non-linear dynamics and high-dimensional configuration space. This work presents a differentiable Material Point Method (MPM) simulator targeted at control…

Robotics · Computer Science 2025-12-16 Diego Bolliger , Gabriele Fadini , Markus Bambach , Alisa Rupenyan

Remotely programming robots to execute tasks often relies on registering objects of interest in the robot's environment. Frequently, these tasks involve articulating objects such as opening or closing a valve. However, existing…

From serving a cup of coffee to positioning mechanical parts during assembly, stable object placement is a crucial skill for future robots. It becomes particularly challenging under geometric uncertainties, e.g., when the object pose or…

Robotics · Computer Science 2025-12-02 Linfeng Li , Gang Yang , Lin Shao , David Hsu

We introduce a modeling framework for manipulation planning based on the formulation of the dynamics as a projected dynamical system. This method uses implicit signed distance functions and their gradients to formulate an equivalent…

Optimization and Control · Mathematics 2025-01-22 Anton Pozharskiy , Armin Nurkanović , Moritz Diehl

This paper presents a robust control scheme for flexible link robotic manipulators, which is based on considering the flexible mechanical structure as a system with slow (rigid) and fast (flexible) modes that can be controlled separately.…

Robotics · Computer Science 2007-05-23 Victor Etxebarria , Arantza Sanz , Ibone Lizarraga

In recent years, the integration of additive manufacturing (AM) and industrial robotics has opened new perspectives for the production of complex components, particularly in the automotive sector. Robot-assisted additive manufacturing…

Robotics · Computer Science 2026-04-03 Alessandro Dimauro , Davide Tebaldi , Fabio Pini , Luigi Biagiotti , Francesco Leali

This paper presents a framework for dynamic object catching using a quadruped robot's front legs while it stands on its rear legs. The system integrates computer vision, trajectory prediction, and leg control to enable the quadruped to…

Robotics · Computer Science 2024-10-11 André Schakkal , Guillaume Bellegarda , Auke Ijspeert

Generalizable manipulation requires that robots be able to interact with novel objects and environment. This requirement makes manipulation extremely challenging as a robot has to reason about complex frictional interaction with uncertainty…

Robotics · Computer Science 2023-01-18 Yuki Shirai , Devesh K. Jha , Arvind Raghunathan , Diego Romeres

This work presents a framework for automatically extracting physical object properties, such as material composition, mass, volume, and stiffness, through robot manipulation and a database of object measurements. The framework involves…

Developing robot controllers in a simulated environment is advantageous but transferring the controllers to the target environment presents challenges, often referred to as the "sim-to-real gap". We present a method for continuous…

Robotics · Computer Science 2022-11-24 Sirui Chen , Keenon Werling , Albert Wu , C. Karen Liu

For dynamic manipulation of flexible objects, we propose an acquisition method of a flexible object motion equation model using a deep neural network and a control method to realize a target state by calculating an optimized time-series…

Robotics · Computer Science 2024-03-25 Kento Kawaharazuka , Toru Ogawa , Juntaro Tamura , Cota Nabeshima

Precision is a crucial performance indicator for robot arms, as high precision manipulation allows for a wider range of applications. Traditional methods for improving robot arm precision rely on error compensation. However, these methods…

Robotics · Computer Science 2023-02-28 Qu Weiming , Liu Tianlin , Luo Dingsheng

Dexterous manipulation requires careful reasoning over extrinsic contacts. The prevalence of deforming tools in human environments, the use of deformable sensors, and the increasing number of soft robots yields a need for approaches that…

Robotics · Computer Science 2025-05-19 Mark Van der Merwe , Miquel Oller , Dmitry Berenson , Nima Fazeli

We present a differentiable dynamics solver that is able to handle frictional contact for rigid and deformable objects within a unified framework. Through a principled mollification of normal and tangential contact forces, our method…

Inspired by the concept of network algebraic connectivity, we adopt an extended notion named rigidity preservation index to characterize the rigidity property for a formation framework. A gradient based controller is proposed to ensure the…

Optimization and Control · Mathematics 2013-09-20 Zhiyong Sun , Changbin Yu , Brian D. O. Anderson

Efficient planning of assembly motions is a long standing challenge in the field of robotics that has been primarily tackled with reinforcement learning and sampling-based methods by using extensive physics simulations. This paper proposes…

Robotics · Computer Science 2026-02-02 Christian Dietz , Sebastian Albrecht , Gianluca Frison , Moritz Diehl , Armin Nurkanović