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Real-time humanoid teleoperation requires inverse kinematics (IK) solvers that are both responsive and constraint-safe under kinematic redundancy and self-collision constraints. While differential IK enables efficient online retargeting,…

Robotics · Computer Science 2026-03-26 Junheng Li , Lizhi Yang , Aaron D. Ames

We introduce a novel quantum computing heuristic for solving the irregular strip packing problem, a significant challenge in optimizing material usage across various industries. This problem involves arranging a set of irregular polygonal…

Quantum Physics · Physics 2024-02-28 Paul-Amaury Matt , Marco Roth

In this work, we present a methodology for devising forward-backward methods for finding zeros in the sum of a finite number of maximally monotone operators. We extend the framework and techniques from [SIAM J. Optim., 34 (2024), pp.…

Optimization and Control · Mathematics 2024-06-06 Francisco J. Aragón-Artacho , Rubén Campoy , César López-Pastor

Collisions are common in many dynamical systems with real applications. They can be formulated as hybrid dynamical systems with discontinuities automatically triggered when states transverse certain manifolds. We present an algorithm for…

Optimization and Control · Mathematics 2025-01-20 Wei Hu , Jihao Long , Yaohua Zang , Weinan E , Jiequn Han

This paper investigates the collaboration of multiple connected and automated vehicles (CAVs) in different scenarios. In general, the collaboration of CAVs can be formulated as a nonlinear and nonconvex model predictive control (MPC)…

Optimization and Control · Mathematics 2022-07-26 Xiaoxue Zhang , Jun Ma , Zilong Cheng , Frank L. Lewis , Tong Heng Lee

This paper presents the open-source robot inverse kinematics (IK) solver IK-Geo, the fastest general IK solver based on published literature. In this unifying approach, IK for any 6-DOF all-revolute (6R) manipulator is decomposed into six…

Robotics · Computer Science 2024-02-20 Alexander J. Elias , John T. Wen

We propose a new operator-sketching paradigm for designing efficient iterative data-driven reconstruction (IDR) schemes, e.g. Plug-and-Play algorithms and deep unrolling networks. These IDR schemes are currently the state-of-the-art…

Image and Video Processing · Electrical Eng. & Systems 2024-12-06 Junqi Tang , Guixian Xu , Subhadip Mukherjee , Carola-Bibiane Schönlieb

Optimal control approaches in combination with trajectory optimization have recently proven to be a promising control strategy for legged robots. Computationally efficient and robust algorithms were derived using simplified models of the…

Robotics · Computer Science 2016-12-28 Alexander Herzog , Stefan Schaal , Ludovic Righetti

We study online statistical inference for the solutions of stochastic optimization problems with equality and inequality constraints. Such problems are prevalent in statistics and machine learning, encompassing constrained $M$-estimation,…

Machine Learning · Statistics 2025-12-11 Yihang Gao , Michael K. Ng , Michael W. Mahoney , Sen Na

This paper presents a kinematic definition of a serialized Stewart platform designed for autonomous in-space assembly called an Assembler. The Assemblers architecture describes problems inherent to the inverse kinematics of over-actuated…

Robotics · Computer Science 2020-03-30 William Chapin , Erik Komendera

High-performance concrete requires complex mix design decisions involving interdependent variables and practical constraints. While data-driven methods have improved predictive modeling for forward design in concrete engineering, inverse…

Machine Learning · Computer Science 2025-12-11 Agung Nugraha , Heungjun Im , Jihwan Lee

To analyze nonlinear dynamic systems, we developed a new technique based on the square matrix method. We propose this technique called the \convergence map" for generating particle stability diagrams similar to the frequency maps widely…

Accelerator Physics · Physics 2023-06-07 Li Hua Yu , Yoshiteru Hidaka , Victor Smaluk

Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled…

We believe that the future of robot motion planning will look very different than how it looks today: instead of complex collision avoidance trajectories with a brittle dependence on sensing and estimation of the environment, motion plans…

Robotics · Computer Science 2021-09-28 Tao Pang , Russ Tedrake

First-order methods for quadratic optimization such as OSQP are widely used for large-scale machine learning and embedded optimal control, where many related problems must be rapidly solved. These methods face two persistent challenges:…

Learning-based control methods for industrial processes leverage the repetitive nature of the underlying process to learn optimal inputs for the system. While many works focus on linear systems, real-world problems involve nonlinear…

Systems and Control · Electrical Eng. & Systems 2023-07-25 Samuel Balula , Efe C. Balta , Dominic Liao-McPherson , Alisa Rupenyan , John Lygeros

We present a geometric framework for the inverse design of smart woven fabrics composed of non-uniformly shrinking threads. A sufficiently tight weaving structure imposes strong local criteria on the material deformation and reduces the…

Soft Condensed Matter · Physics 2026-01-23 Einav Berin , Hillel Aharoni

With new advancements in interaction techniques, character animation also requires new methods, to support fields such as robotics, and VR/AR. Interactive characters in such fields are becoming driven by AI which opens up the possibility of…

Robotics · Computer Science 2019-11-19 Tiago Ribeiro , Ana Paiva

In the last years, several hierarchical frameworks have been proposed to deal with highly-redundant robotic systems. Some of that systems are expected to perform multiple tasks and physically to interact with the environment. However, none…

Robotics · Computer Science 2022-04-06 Juan David Munoz-Osorio , Felix Allmendinger

Joint space trajectory optimization under end-effector task constraints leads to a challenging non-convex problem. Thus, a real-time adaptation of prior computed trajectories to perturbation in task constraints often becomes intractable.…