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Training long-horizon robotic policies in complex physical environments is essential for many applications, such as robotic manipulation. However, learning a policy that can generalize to unseen tasks is challenging. In this work, we…

Machine Learning · Computer Science 2023-06-01 Stone Tao , Xiaochen Li , Tongzhou Mu , Zhiao Huang , Yuzhe Qin , Hao Su

It is known that pure row contractions with one-dimensional defect spaces can be classified up to unitary equivalence by compressions of the standard $d$-shift acting on the full Fock space. Upon settling for a softer relation than unitary…

Functional Analysis · Mathematics 2018-09-10 Raphaël Clouâtre , Edward J. Timko

Distributed optimization consists of multiple computation nodes working together to minimize a common objective function through local computation iterations and network-constrained communication steps. In the context of robotics,…

Robotics · Computer Science 2021-03-25 Trevor Halsted , Ola Shorinwa , Javier Yu , Mac Schwager

Recent advancements in adaptive control for reference trajectory tracking enable quadrupedal robots to perform locomotion tasks under challenging conditions. There are methods enabling the estimation of the external disturbances in terms of…

Robotics · Computer Science 2025-05-20 Elizaveta Pestova , Ilya Osokin , Danil Belov , Pavel Osinenko

The Discrete Dislocation (DD) analysis and its computional modeling have been advanced significantly over the past decade. This progress has been further magnified by the idea to couple DD with continuum mechanics analysis in association…

Materials Science · Physics 2007-05-23 H. M. Zbib , M. Hiratani , M. Shehade

Tilt-rotor aerial robots enable omnidirectional maneuvering through thrust vectoring, but introduce significant control challenges due to the strong coupling between joint and rotor dynamics. While model-based controllers can achieve high…

Robotics · Computer Science 2026-02-26 Wentao Zhang , Zhaoqi Ma , Jinjie Li , Huayi Wang , Haokun Liu , Junichiro Sugihara , Chen Chen , Yicheng Chen , Moju Zhao

Automatic data abstraction is an important capability for both benchmarking machine intelligence and supporting summarization applications. In the former one asks whether a machine can `understand' enough about the meaning of input data to…

Computer Vision and Pattern Recognition · Computer Science 2019-08-09 Umar Riaz Muhammad , Yongxin Yang , Timothy M. Hospedales , Tao Xiang , Yi-Zhe Song

This paper presents an object manipulation strategy for the Variable Topology Truss (VTT) system, a truss robot that comprises actuated truss members connected by passive spherical joints. Although truss robots were originally proposed as…

Robotics · Computer Science 2026-05-14 Andrew Jang-Ho Bae , Myeongjin Choi , Haorui Li , Mark Yim , TaeWon Seo

This paper studies the construction of dynamic symbolic abstractions for nonlinear control systems via dynamic quantization. Since computational complexity is a fundamental problem in the use of discrete abstractions, a dynamic quantizer…

Systems and Control · Electrical Eng. & Systems 2020-11-26 Wei Ren , Dimos V. Dimarogonas

A metamorphic robotic system is an aggregate of homogeneous robot units which can individually and selectively locomote in such a way as to change the global shape of the system. We introduce a mathematical framework for defining and…

Robotics · Computer Science 2007-05-23 A. Abrams , R. Ghrist

Objects' rigid motions in 3D space are described by rotations and translations of a highly-correlated set of points, each with associated $x,y,z$ coordinates that real-valued networks consider as separate entities, losing information.…

Artificial Intelligence · Computer Science 2023-10-12 Guilherme Vieira , Eleonora Grassucci , Marcos Eduardo Valle , Danilo Comminiello

Single locomotion robots often struggle to adapt in highly variable or uncertain environments, especially in emergencies. In this paper, a multi-modal deformable robot is introduced that can both fly and drive. Compatibility issues with…

Robotics · Computer Science 2023-02-14 Xinyu Zhang , Yuanhao Huang , Kangyao Huang , Xiaoyu Wang , Dafeng Jin , Huaping Liu , Jun Li

This paper presents a nonlinear control design for highly underactuated balance robots, which possess more numbers of unactuated degree-of-freedom (DOF) than actuated ones. To address the challenge of simultaneously trajectory tracking of…

Robotics · Computer Science 2023-10-03 Feng Han , Jingang Yi

We introduce the notion of a contractible subshift. This is a strengthening of the notion of strong irreducibility, where we require that the gluings are given by a block map. We show that a subshift is a retract of a full shift if and only…

Dynamical Systems · Mathematics 2026-04-24 Leo Poirier , Ville Salo

To enlarge the translational workspace of cable-driven robots, one common approach is to increase the number of cables. However, this introduces two challenges: (1) cable interference significantly reduces the rotational workspace, and (2)…

Robotics · Computer Science 2025-11-04 Nan Zhang

Shifted combinatorial optimization is a new nonlinear optimization framework, which is a broad extension of standard combinatorial optimization, involving the choice of several feasible solutions at a time. It captures well studied and…

Optimization and Control · Mathematics 2017-06-08 Martin Koutecky , Asaf Levin , Syed M. Meesum , Shmuel Onn

Finite-state abstractions (a.k.a. symbolic models) present a promising avenue for the formal verification and synthesis of controllers in continuous-space control systems. These abstractions provide simplified models that capture the…

Systems and Control · Electrical Eng. & Systems 2025-02-25 Daniel Ajeleye , Majid Zamani

A hybrid continuum robot design is introduced that combines a proximal tendon-actuated section with a distal telescoping section comprised of permanent-magnet spheres actuated using an external magnet. While, individually, each section can…

The low displacement rank (LDR) framework for structured matrices represents a matrix through two displacement operators and a low-rank residual. Existing use of LDR matrices in deep learning has applied fixed displacement operators…

Machine Learning · Computer Science 2019-01-03 Anna T. Thomas , Albert Gu , Tri Dao , Atri Rudra , Christopher Ré

This paper introduces abstractions that are meaningful for computers and that can be built and used according to computers' own criteria, i.e., computable abstractions. It is analyzed how abstractions can be seen to serve as the building…

Artificial Intelligence · Computer Science 2015-03-31 Alejandro Sanchez Guinea