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We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the…

Simplified models are useful to increase the computational efficiency of a motion planning algorithm, but their lack of accuracy have to be managed. We propose two feasibility constraints to be included in a Single Rigid Body Dynamicsbased…

In this series of papers, we present a motion planning framework for planning comfortable and customizable motion of nonholonomic mobile robots such as intelligent wheelchairs and autonomous cars. In this first one we present the…

Robotics · Computer Science 2013-05-23 Shilpa Gulati , Chetan Jhurani , Benjamin Kuipers

Orthogonality constraints are ubiquitous in robust and probabilistic machine learning. Unfortunately, current optimizers are computationally expensive and do not scale to problems with hundreds or thousands of constraints. One notable…

Machine Learning · Computer Science 2026-02-17 Adrián Javaloy , Antonio Vergari

Analytic and optimization methods for solving inverse kinematics (IK) problems have been deeply studied throughout the history of robotics. The two strategies have complementary strengths and weaknesses, but developing a unified approach to…

Robotics · Computer Science 2026-02-06 Thomas Cohn , Lihan Tang , Alexandre Amice , Russ Tedrake

This work casts the kinodynamic planning problem for car-like vehicles as an optimization task to compute a minimum-time trajectory and its associated velocity profile, subject to boundary conditions on velocity, acceleration, and steering.…

Robotics · Computer Science 2025-08-25 Otobong Jerome , Alexandr Klimchik , Alexander Maloletov , Geesara Kulathunga

Industrial robots are increasingly deployed in applications requiring an end effector tool to closely track a specified path, such as in spraying and welding. Performance and productivity present possibly conflicting objectives: tracking…

Robotic systems are routinely used in the logistics industry to enhance operational efficiency, but the design of robot workspaces remains a complex and manual task, which limits the system's flexibility to changing demands. This paper aims…

Robotics · Computer Science 2025-03-10 Peiyu Zeng , Yijiang Huang , Simon Huber , Stelian Coros

This paper explores general multi-robot task and motion planning, where multiple robots in close proximity manipulate objects while satisfying constraints and a given goal. In particular, we formulate the plan refinement problem--which,…

Robotics · Computer Science 2023-09-19 Yoonchang Sung , Rahul Shome , Peter Stone

A basic task in the design of a robotic production cell is the relative placement of robot and workpiece. The fundamental requirement is that the robot can reach all process positions; only then one can think of further optimization.…

Robotics · Computer Science 2019-01-03 Martin Weiß

Trajectory optimization is the core of modern model-based robotic control and motion planning. Existing trajectory optimizers, based on sequential quadratic programming (SQP) or differential dynamic programming (DDP), are often limited by…

Robotics · Computer Science 2026-03-03 Haizhou Zhao , Ludovic Righetti , Majid Khadiv

In this paper, we demonstrate a formulation for optimizing coupled submodular maximization problems with provable sub-optimality bounds. In robotics applications, it is quite common that optimization problems are coupled with one another…

Robotics · Computer Science 2021-11-19 Jun Liu , Ryan K. Williams

We present a batch trajectory optimizer that can simultaneously solve hundreds of different instances of the problem in real-time. We consider holonomic robots but relax the assumption of circular base footprint. Our main algorithmic…

Robotics · Computer Science 2021-09-28 Fatemeh Rastgar , Houman Masnavi , Karl Kruusamäe , Alvo Aabloo , Arun Kumar Singh

This paper addresses the kinodynamic motion planning for non-holonomic robots in dynamic environments with both static and dynamic obstacles -- a challenging problem that lacks a universal solution yet. One of the promising approaches to…

Robotics · Computer Science 2023-01-02 Brian Angulo , Aleksandr Panov , Konstantin Yakovlev

Significant effort has been made to solve computationally expensive optimization problems in the past two decades, and various optimization methods incorporating surrogates into optimization have been proposed. However, most optimization…

Neural and Evolutionary Computing · Computer Science 2022-04-13 Julian Blank , Kalyanmoy Deb

This work considers a Motion Planning Problem with Dynamic Obstacles (MPDO) in 2D that requires finding a minimum-arrival-time collision-free trajectory for a point robot between its start and goal locations amid dynamic obstacles moving…

Robotics · Computer Science 2022-06-03 Zhongqiang Ren , Sivakumar Rathinam , Howie Choset

The levels of agility and flight or swimming performance demonstrated by insects, birds, fish, and even some aquatic invertebrates, are often vastly superior to what even the most advanced human-engineered vehicles operating in the same…

Fluid Dynamics · Physics 2021-12-21 Christoph Busch , Alexander Gehrke , Karen Mulleners

This paper proposes a control method to address the physical Human-Robot Interaction (pHRI) challenge in the context of hierarchical tasks. A common approach to managing hierarchical tasks is Hierarchical Quadratic Programming (HQP), which,…

Robotics · Computer Science 2024-10-23 Mengxin Xu , Weiwei Wan , Hesheng Wang , Kensuke Harada

Optimizing application performance in today's hardware architecture landscape is an important, but increasingly complex task, often requiring detailed performance analyses. In particular, data movement and reuse play a crucial role in…

Software Engineering · Computer Science 2023-06-29 Philipp Schaad , Tal Ben-Nun , Torsten Hoefler

Understanding human intentions is critical for safe and effective human-robot collaboration. While state of the art methods for human goal prediction utilize learned models to account for the uncertainty of human motion data, that data is…

Robotics · Computer Science 2024-01-24 Yi-Shiuan Tung , Matthew B. Luebbers , Alessandro Roncone , Bradley Hayes