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Approximate dynamic programming has been investigated and used as a method to approximately solve optimal regulation problems. However, the extension of this technique to optimal tracking problems for continuous time nonlinear systems has…

Systems and Control · Computer Science 2017-07-25 Rushikesh Kamalapurkar , Huyen Dinh , Shubhendu Bhasin , Warren Dixon

This work addresses the problem of predicting the motion trajectories of dynamic objects in the environment. Recent advances in predicting motion patterns often rely on machine learning techniques to extrapolate motion patterns from…

Robotics · Computer Science 2021-07-12 Weiming Zhi , Lionel Ott , Fabio Ramos

Terrain geometry is, in general, non-smooth, non-linear, non-convex, and, if perceived through a robot-centric visual unit, appears partially occluded and noisy. This work presents the complete control pipeline capable of handling the…

Robotics · Computer Science 2022-07-06 Fabian Jenelten , Ruben Grandia , Farbod Farshidian , Marco Hutter

We study network design problems for nonlinear and nonconvex flow models without controllable elements under load scenario uncertainties, i.e., under uncertain injections and withdrawals. To this end, we apply the concept of adjustable…

Optimization and Control · Mathematics 2025-01-20 Johannes Thürauf , Julia Grübel , Martin Schmidt

With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have…

Robotics · Computer Science 2025-03-12 Mengke Zhang , Zhihao Tian , Yaoguang Xia , Chao Xu , Fei Gao , Yanjun Cao

This paper presents a new trajectory replanner for grasping irregular objects. Unlike conventional grasping tasks where the object's geometry is assumed simple, we aim to achieve a "dynamic grasp" of the irregular objects, which requires…

Robotics · Computer Science 2025-01-31 Minh Nhat Vu , Florian Grander , Anh Nguyen

To be applicable to real world scenarios trajectory planning schemes for mobile autonomous systems must be able to efficiently deal with obstacles in the area of operation. In the context of optimization based trajectory planning and…

Optimization and Control · Mathematics 2021-04-27 Max Lutz , Thomas Meurer

Offline optimal planning of trajectories for redundant robots along prescribed task space paths is usually broken down into two consecutive processes: first, the task space path is inverted to obtain a joint space path, then, the latter is…

Robotics · Computer Science 2023-12-13 Enrico Ferrentino , Heitor J. Savino , Antonio Franchi , Pasquale Chiacchio

This paper presents a computational framework for the robust stiffness design of hyperelastic structures at finite deformations subject to various uncertain sources. In particular, the loading, material properties, and geometry…

Computational Engineering, Finance, and Science · Computer Science 2025-01-28 Nan Feng , Guodong Zhang , Kapil Khandelwal

Inspired by sled-pulling dogs in transportation, we present a cable-trailer integrated with a quadruped robot system. The motion planning of this system faces challenges due to the interactions between the cable's state transitions, the…

Robotics · Computer Science 2025-12-23 Wentao Zhang , Shaohang Xu , Gewei Zuo , Bolin Li , Jingbo Wang , Lijun Zhu

A cable-driven soft-bodied robot with redundancy can conduct the trajectory tracking task and in the meanwhile fulfill some extra constraints, such as tracking through an end-effector in designated orientation, or get rid of the evitable…

Robotics · Computer Science 2022-01-21 Jiewen Lai , Bo Lu , Qingxiang Zhao , Henry K. Chu

Multi robot systems have the potential to be utilized in a variety of applications. In most of the previous works, the trajectory generation for multi robot systems is implemented in known environments. To overcome that we present an online…

Robotics · Computer Science 2018-12-04 Vijay Arvindh , Govind Aadithya R , Shravan Krishnan , Sivanathan K

Iterative trajectory optimization techniques for non-linear dynamical systems are among the most powerful and sample-efficient methods of model-based reinforcement learning and approximate optimal control. By leveraging time-variant local…

Systems and Control · Electrical Eng. & Systems 2019-08-01 Onur Celik , Hany Abdulsamad , Jan Peters

Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant challenges for quadruped robots. This paper introduces a robust locomotion framework for safe navigation over unstable surfaces by…

We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key contribution is a control-theoretic regularizer for dynamics fitting rooted in the notion of…

Optimization and Control · Mathematics 2019-08-01 Sumeet Singh , Spencer M. Richards , Vikas Sindhwani , Jean-Jacques E. Slotine , Marco Pavone

Dynamic maneuvers for legged robots present a difficult challenge due to the complex dynamics and contact constraints. This paper introduces a versatile trajectory optimization framework for continuous-time multi-phase problems. We…

Robotics · Computer Science 2024-09-20 Ethan Chandler , Akshay Jaitly , Mahdi Agheli

In this paper we present a method for automatically generating optimal robot trajectories satisfying high level mission specifications. The motion of the robot in the environment is modeled as a general transition system, enhanced with…

Robotics · Computer Science 2010-07-16 Stephen L. Smith , Jana Tumova , Calin Belta , Daniela Rus

We consider optimal transport based distributionally robust optimization (DRO) problems with locally strongly convex transport cost functions and affine decision rules. Under conventional convexity assumptions on the underlying loss…

Optimization and Control · Mathematics 2021-04-27 Jose Blanchet , Karthyek Murthy , Fan Zhang

This paper presents a chance-constrained formulation for robust trajectory optimization during manipulation. In particular, we present a chance-constrained optimization for Stochastic Discrete-time Linear Complementarity Systems (SDLCS). To…

Robotics · Computer Science 2022-03-08 Yuki Shirai , Devesh K. Jha , Arvind Raghunathan , Diego Romeres

Planning a time-optimal trajectory for aerial robots is critical in many drone applications, such as rescue missions and package delivery, which have been widely researched in recent years. However, it still involves several challenges,…

Robotics · Computer Science 2022-09-02 Wei Luo , Jingshan Chen , Henrik Ebel , Peter Eberhard
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