检索结果-内蒙古大学图书馆

Nonsmooth Trajectory optimization for Wheeled Balancing Robots With Contact Switches and Impacts

IEEE TRANSACTIONS ON ROBOTICS 2025年 41卷 497-517页

作者： Klemm, Victor de Viragh, Yvain Rohr, David Siegwart, Roland Tognon, Marco Swiss Fed Inst Technol ASL CH-8092 Zurich Switzerland Swiss Fed Inst Technol RSL CH-8092 Zurich Switzerland INRIA Rennes Rainbow Team F-35042 Rennes France

Recent years have seen a steady rise in the abilities of wheeled-legged balancing robots. Yet, their use is still severely restricted by the lack of efficient control algorithms for overcoming obstacles such as stairs. We take a considerable step toward closing this gap by presenting a fast trajectory optimizer for generating trajectories over a large class of challenging terrains. By limiting the underlying modeling to the planar, nonlinear rigid-body dynamics and subdividing the terrain into contact-phases, a tractable nonlinear programming problem is obtained. The model explicitly accounts for contact switches and impacts, traction limits, and actuation bounds. By introducing an arc-length-related parametrization, the trajectories are rendered inherently contact constraint-consistent. We apply our method to the specific case of the wheeled bipedal robot Ascento, for which we derive closed-form expressions of the dynamics equations, including the kinematic loops. To track the trajectories, we propose a simple LQR-based controller. The approach is validated in real-world experiments where we show the execution of trajectories for traversing steps, driving up ramps, jumping, standing up, and driving up entire stairways. To the best of our knowledge, enabling the latter by means of trajectory optimization (TO) is a novelty for wheeled-legged robots.

关键词： Robots Trajectory Legged locomotion Mathematical models Quadrupedal robots Stairs Tracking Contact modeling legged robots optimization and optimal control wheeled robots

来源：评论

学校读者我要写书评

暂无评论

optimal Design of High-Dynamic Robotic Arm Based on Angular Momentum Maximum

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第4期10卷 3542-3549页

作者： Yuan, Yanyan Liu, Xianwei Jiang, Lei Jin, Yongbin Wang, Hongtao Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310012 Peoples R China Zhejiang Univ Ctr Mechan 10 Hangzhou 310012 Peoples R China Zhejiang Univ Inst Appl Mech Hangzhou 310012 Peoples R China ZJU Hangzhou Global Sci & Technol Innovat Ctr Hangzhou 311200 Peoples R China

In industrial applications, precision and load capacity are critical performance metrics for robotic arms. These requirements are typically addressed using high-gear-ratio designs. However, robotic arms are increasingly tasked with high-dynamic operations, such as smashes in sports and object throwing, where traditional design paradigms and evaluation metrics are insufficient. Drawing inspiration from the dynamics of ball sports, we establish an optimization design paradigm for high-dynamic robotic arms by introducing angular momentum as performance metric. Based on this paradigm, we developed a 7-DOF robotic arm, KirinArm, and evaluated its performance in a badminton swinging task. KirinArm achieves a maximum end-effector speed of 10.1 m/s and a peak acceleration of 234.7 m/s(2), outperforming known commercial collaborative robotic arms. Notably, its racket tip reaches a speed of 31.3 m/s, equivalent to the level of an amateur badminton player and 48.45% of the performance of professional athletes under similar conditions. Comparative analysis with five other robotic arms, based on maximum angular momentum and acceleration metrics, highlights KirinArm's superior performance, even under increased dynamic loads.

关键词： Manipulators Robots optimization Torque Motors Sports Measurement Gears Dynamics Wrist optimization and optimal control dynamics performance evaluation and benchmarking

来源：评论

学校读者我要写书评

暂无评论

Interpreting and Improving optimal control Problems With Directional Corrections

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第5期10卷 4986-4993页

作者： Barron, Trevor Zhang, Xiaojing Apple Inc Cupertino CA 95014 USA

Many robotics tasks, such as path planning or trajectory optimization, are formulated as optimal control problems (OCPs). The key to obtaining high performance lies in the design of the OCP's objective function. In practice, the objective function consists of a set of individual components that must be carefully modeled and traded off such that the OCP has the desired solution. It is often challenging to balance multiple components to achieve the desired solution and to understand, when the solution is undesired, the impact of individual cost components. In this paper, we present a framework addressing these challenges based on the concept of directional corrections. Specifically, given the solution to an OCP that is deemed undesirable, and access to an expert providing the direction of change that would increase the desirability of the solution, our method analyzes the individual cost components for their "consistency" with the provided directional correction. This information can be used to improve the OCP formulation, e.g., by increasing the weight of consistent cost components, or reducing the weight of - or even redesigning - inconsistent cost components. We also show that our framework can automatically tune parameters of the OCP to achieve consistency with a set of corrections.

关键词： Costs Robots Linear programming optimal control Gold Cost function Trajectory System dynamics Linear systems Training optimization and optimal control motion and path planning machine learning for robot control autonomous agents

来源：评论

学校读者我要写书评

暂无评论

Efficient safety-critical trajectory planning for any N-trailer system with a general model

引用

control ENGINEERING PRACTICE 2025年 158卷

作者： Gao, Liang Jia, Bobo Li, Daiwei Yang, Yi Xie, Shanshan Beijing Inst Technol Coll Automat Beijing 100081 Peoples R China

Trajectory planning for tractor-trailer vehicles (TTVs) in a cluttered environment is a highly challenging task owing to complicated kinematic and large-scale collision-avoidance constraints. It has stringent requirements for trajectory feasibility and computational efficiency. Moreover, the varying configurations of TTVs pose challenges to the scalability of the planning method. This article proposes a novel safety-critical trajectory planning method with a general model to address these challenges. Firstly, an algebraic general model is first presented to represent these N-Trailer systems with different hitching types and trailer types uniformly. Secondly, the planning problem is formulated as a nonlinear model predictive control scheme with two key efforts to accelerate calculation speed. One operation is that a novel search-guided optimization-based collision avoidance (SG-OBCA) method is developed to provide a high-quality initial guess. The other operation is that intractable non-convex collision-avoidance constraints are translated into a dual form based on exponential discrete-time control barrier function (DCBF). Finally, both comparative simulations and real-world experiments are conducted to demonstrate the efficiency and applicability of the proposed method indifferent complicated scenarios and configurations of TTVs.

关键词： optimization and optimal control Tractor-trailer vehicle Nonholonomic motion planning General model control barrier function

来源：评论

学校读者我要写书评

暂无评论

ProxDDP: Proximal Constrained Trajectory optimization

引用

IEEE TRANSACTIONS ON ROBOTICS 2025年 41卷 2605-2624页

作者： Jallet, Wilson Bambade, Antoine Arlaud, Etienne El-Kazdadi, Sarah Mansard, Nicolas Carpentier, Justin PSL Res Univ Inria Dept Informat Ecolenormale Super F-75006 Paris France LAAS CNRS F-75006 Toulouse France

Trajectory optimization has been a popular choice for motion generation and control in robotics for at least a decade. Several numerical approaches have exhibited the required speed to enable online computation of trajectories for real-time of various systems, including complex robots. Many of these said are based on the differential dynamic programming (DDP) algorithm-initially designed for unconstrained trajectory optimization problems-and its variants, which are relatively easy to implement and provide good runtime performance. However, several problems in robot control call for using constrained formulations (e.g., torque limits, obstacle avoidance), from which several difficulties arise when trying to adapt DDP-type methods: numerical stability, computational efficiency, and constraint satisfaction. In this article, we leverage proximal methods for constrained optimization and introduce a DDP-type method for fast, constrained trajectory optimization suited for model-predictive control (MPC) applications with easy warm-starting. Compared to earlier solvers, our approach effectively manages hard constraints without warm-start limitations and exhibits good convergence behavior. We provide a complete implementation as part of an open-source and flexible C++ trajectory optimization library called aligator. These algorithmic contributions are validated through several trajectory planning scenarios from the robotics literature and the real-time whole-body MPC of a quadruped robot.

关键词： Legged robots model-predictive control (MPC) optimization and optimal control optimization and optimal control optimization and optimal control

来源：评论

学校读者我要写书评

暂无评论

Constrained Articulated Body Dynamics Algorithms

引用

IEEE TRANSACTIONS ON ROBOTICS 2025年 41卷 430-449页

作者： Sathya, Ajay Suresha Carpentier, Justin PSL Res Univ Ecole Normale Super Inria Dept Informat F-75006 Paris France Katholieke Univ Leuven Dept Mech Engn MECO Res Team B-3001 Leuven Belgium Katholieke Univ Leuven Flanders Make B-3001 Leuven Belgium

Rigid-body dynamics algorithms have played an essential role in robotics development. By finely exploiting the underlying robot structure, they allow the computation of the robot kinematics, dynamics, and related physical quantities with low complexity, enabling their integration into chipsets with limited resources or their evaluation at very high frequency for demanding applications (e.g., model predictive control, large-scale simulation, reinforcement learning, etc.). While most of these algorithms operate on constraint-free settings, only a few have been proposed so far to adequately account for constrained dynamical systems while depicting low algorithmic complexity. In this article, we introduce a series of new algorithms with reduced (and lowest) complexity for the forward simulation of constrained dynamical systems. Notably, we revisit the so-called articulated body algorithm (ABA) and the Popov-Vereshchagin algorithm (PV) in the light of proximal-point optimization and introduce two new algorithms, called constrained ABA and proxPV. These two new algorithms depict linear complexities while being robust to singular cases (e.g., redundant constraints, singular constraints, etc.). We establish the connection with existing literature formulations, especially the relaxed formulation at the heart of the MuJoCo and Drake simulators. We also propose an efficient and new algorithm to compute the damped Delassus inverse matrix with the lowest known computational complexity. All these algorithms have been implemented inside the open-source framework Pinocchio and depict, on a wide range of robotic systems ranging from robot manipulators to complex humanoid robots, state-of-the-art performances compared to alternative solutions of the literature.

关键词： Heuristic algorithms Robots Robot kinematics Symmetric matrices Vectors Prediction algorithms Kinematics Computational efficiency Computational complexity Symbols Direct/inverse dynamics formulation dynamics humanoid robots optimization and optimal control

来源：评论

学校读者我要写书评

暂无评论

A Tutorial on Distributed optimization for Cooperative Robotics: From Setups and Algorithms to Toolboxes and Research Directions

引用

PROCEEDINGS OF THE IEEE 2025年第1期113卷 40-65页

作者： Testa, Andrea Carnevale, Guido Notarstefano, Giuseppe Univ Bologna Dept Elect Elect & Informat Engn I-40136 Bologna Italy

Several interesting problems in multirobot systems can be cast in the framework of distributed optimization. Examples include multirobot task allocation, vehicle routing, target protection, and surveillance. While the theoretical analysis of distributed optimization algorithms has received significant attention, its application to cooperative robotics has not been investigated in detail. In this article, we show how notable scenarios in cooperative robotics can be addressed by suitable distributed optimization setups. Specifically, after a brief introduction on the widely investigated consensus optimization (most suited for data analytics) and on the partition-based setup (matching the graph structure in the optimization), we focus on two distributed settings modeling several scenarios in cooperative robotics, i.e., the so-called constraint-coupled and aggregative optimization frameworks. For each one, we consider use-case applications, and we discuss tailored distributed algorithms with their convergence properties. Then, we revise state-of-the-art toolboxes allowing for the implementation of distributed schemes on real networks of robots without central coordinators. For each use case, we discuss its implementation in these toolboxes and provide simulations and real experiments on networks of heterogeneous robots.

关键词： optimization Robots Multi-robot systems Robot kinematics Surveillance Resource management Distributed algorithms Tutorials Formation control Vehicle routing Cooperating robots distributed optimization distributed robot systems optimization and optimal control

来源：评论

学校读者我要写书评

暂无评论

Pushing Everything Everywhere All at Once: Probabilistic Prehensile Pushing

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第5期10卷 4540-4547页

作者： Perugini, Patrizio Lundell, Jens Friedl, Katharina Kragic, Danica KTH SE-10044 Stockholm Sweden Flanders Make B-3001 Leuven Belgium Kungliga Tekn Hogskolan KTH Div Robot Percept & Learning SE-10044 Stockholm Brazil

We address prehensile pushing, the problem of manipulating a grasped object by pushing against the environment. Our solution is an efficient nonlinear trajectory optimization problem relaxed from an exact mixed integer non-linear trajectory optimization formulation. The critical insight is recasting the external pushers (environment) as a discrete probability distribution instead of binary variables and minimizing the entropy of the distribution. The probabilistic reformulation allows all pushers to be used simultaneously, but at the optimum, the probability mass concentrates onto one due to the entropy minimization. We numerically compare our method against a state-of-the-art sampling-based baseline on a prehensile pushing task. The results demonstrate that our method finds trajectories 8 times faster and at a 20 times lower cost than the baseline. Finally, we demonstrate that a simulated and real Frank Panda robot can successfully manipulate different objects following the trajectories proposed by our method.

关键词： Friction Trajectory optimization Entropy Dynamics Gravity Vectors Torque Probabilistic logic Planning Manipulator dynamics Dexterous manipulation optimization and optimal control manipulation planning

来源：评论

学校读者我要写书评

暂无评论

Robust Dynamic Walking for Humanoid Robots via Computationally Efficient Footstep Planner and Whole-Body control

引用

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2025年第2期111卷 1-21页

作者： Wang, Xiangji Guo, Wei Zhang, Teng Zheng, Weicong He, Zhicheng Zha, Fusheng Wang, Pengfei Sun, Lining Harbin Inst Technol HIT State Key Lab Robot & Syst Harbin 150001 Heilongjiang Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Optimizat Control & Int Harbin 150080 Heilongjiang Peoples R China Harbin Inst Technol HIT Fac Comp Harbin 150001 Heilongjiang Peoples R China

The robust dynamic walking control of humanoid robots is the foundation for their application in complex scenarios. Model Predictive control (MPC) can predict the robot's motion state over a future time horizon to obtain optimal control inputs and has achieved significant success in walking control of legged robots. However, the high computational cost makes it challenging to ensure real-time performance when dealing with complex dynamic systems. A novel dynamic walking control framework for humanoid robots is introduced in this paper by integrating an efficient footstep planner and Task Space Inverse Dynamics based Whole Body controller (TSID-WBC). This framework aims to enhance the dynamic performance and robustness of the humanoid robot's walking control. Firstly, design a bionic step time generator based on relevant research in biology. Then, the MPC controller, combined with the differential equation solution of the Linear Inverted Pendulum (LIP) dynamics model, is used to predict the optimal footsteps for the humanoid robot. Finally, TSID-WBC is employed to optimize joint torques, joint accelerations, and generalized contact forces based on predefined task priorities. The proposed framework avoids using MPC for predictive control of complex dynamic models. Instead, it innovatively integrates the bionic step time generator proposed in this paper with an MPC based on the differential solution of the LIP dynamics model, resulting in an efficient footstep planner. The simulation and experimental results of the humanoid robot Kuavo demonstrate that the proposed control framework achieves better tracking performance for desired walking speeds and responds quickly to external disturbances.

关键词： Humanoid robots Walking control Step time generator optimization and optimal control

来源：评论

学校读者我要写书评

暂无评论

Maximising Tolerance to Disturbances via Combined control-Actuation Optimisation for Robust Humanoid Robot Walking

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第5期10卷 4348-4355页

作者： Sathuluri, Akhil Sartore, Carlotta Dafarra, Stefano Traversaro, Silvio Zimmermann, Markus Pucci, Daniele Tech Univ Munich TUM Sch Engn & Design Lab Prod Dev & Lightweight Design Robot Syst Grp D-80333 Munich Germany Ctr Robot Technol Inst Italiano Technol Artificial & Mech Intelligence I-16163 Genoa Italy

Combined optimisation of various robot subsystems as a co-design problem has been shown to identify performant robots. However, classical optimisation methods result in point-optimum solutions that may not ensure robust performance and physical feasibility, i.e., the existence of components with specifications matching the computed optimum value. To address this problem, we present a set-based robust co-design optimisation strategy to maximise disturbance tolerance. Instead of identifying a single point-optimum solution, a so-called solution space evaluates the combination of the largest design space that delivers the necessary performance while being robust to the largest set of disturbances. The utility of the proposed approach is demonstrated via a computational design study of the ergoCub robot. This study focuses on the robots' walking performance, illustrating (1) improvement in task success considering at least 3 times larger magnitudes of disturbances, (2) identifying a set instead of a point-solution in the design-disturbances space, and (3) improving standardisation of the joint actuation design.

关键词： Robots optimization Legged locomotion Voltage control Motors Aerospace electronics Torque Gears Collision avoidance Humanoid robots Humanoid robot systems optimization and optimal control methods and tools for robot system design

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：