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We consider the problem of optimal path planning in different homotopy classes in a given environment. Though important in robotics applications, path-planning with reasoning about homotopy classes of trajectories has typically focused on…

机器人学 · 计算机科学 2017-10-10 Subhrajit Bhattacharya , Robert Ghrist

Robot swarms navigating through unknown obstacle environments are an emerging research area that faces challenges. Performing tasks in such environments requires swarms to achieve autonomous localization, perception, decision-making,…

机器人学 · 计算机科学 2026-04-27 Pengda Mao , Shuli Lv , Chen Min , Zhaolong Shen , Quan Quan

This paper presents a systematic approach for computing local solutions to motion planning problems in non-convex environments using numerical optimal control techniques. It extends the range of use of state-of-the-art numerical optimal…

最优化与控制 · 数学 2017-10-03 Kristoffer Bergman , Daniel Axehill

This paper addresses path set planning that yields important applications in robot manipulation and navigation such as path generation for deformable object keypoints and swarms. A path set refers to the collection of finite agent paths to…

机器人学 · 计算机科学 2024-07-12 Jing Huang , Yunxi Tang , Kwok Wai Samuel Au

This work presents an efficient method to solve a class of continuous-time, continuous-space stochastic optimal control problems of robot motion in a cluttered environment. The method builds upon a path integral representation of the…

系统与控制 · 计算机科学 2016-03-10 Jung-Su Ha , Han-Lim Choi

Safe navigation within a workspace is a fundamental skill for autonomous robots to accomplish more complex tasks. Harmonic potentials are artificial potential fields that are analytical, globally convergent and provably free of local…

机器人学 · 计算机科学 2025-07-15 Shuaikang Wang , Tiecheng Guo , Meng Guo

Safe navigation in cluttered environments is an important challenge for autonomous systems. Robots navigating through obstacle ridden scenarios need to be able to navigate safely in the presence of obstacles, goals, and ego objects of…

系统与控制 · 电气工程与系统科学 2026-05-05 Omanshu Thapliyal , Malarvizhi Sankaranarayanasamy , Ravigopal Vennelakanti

Path planning has long been one of the major research areas in robotics, with PRM and RRT being two of the most effective classes of planners. Though generally very efficient, these sampling-based planners can become computationally…

机器人学 · 计算机科学 2023-05-26 Sipu Ruan , Karen L. Poblete , Hongtao Wu , Qianli Ma , Gregory S. Chirikjian

In this work, we present a workspace-based planning framework, which though using redundant workspace key-points to represent robot states, can take advantage of the interpretable geometric information to derive good quality collision-free…

机器人学 · 计算机科学 2022-06-17 Weifu Wang , Ping Li

We study the navigation problem for a robot moving amidst static and dynamic obstacles and rely on a hierarchical approach to solve it. First, the reference trajectory is planned by the safe interval path planning algorithm that is capable…

机器人学 · 计算机科学 2019-06-18 Konstantin Yakovlev , Anton Andreychuk , Juliya Belinskaya , Dmitry Makarov

We study the computational complexity of optimally solving multi-robot path planning problems on planar graphs. For four common time- and distance-based objectives, we show that the associated path optimization problems for multiple robots…

机器人学 · 计算机科学 2015-12-08 Jingjin Yu

We study the path planning problem for continuum-arm robots, in which we are given a starting and an end point, and we need to compute a path for the tip of the continuum arm between the two points. We consider both cases where obstacles…

机器人学 · 计算机科学 2018-12-11 Jiahao Deng , Brandon H. Meng , Iyad Kanj , Isuru S. Godage

Despite recent progress on trajectory planning of multiple robots and path planning of a single tethered robot, planning of multiple tethered robots to reach their individual targets without entanglements remains a challenging problem. In…

机器人学 · 计算机科学 2023-04-26 Muqing Cao , Kun Cao , Shenghai Yuan , Thien-Minh Nguyen , Lihua Xie

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an…

Tethered robots play a pivotal role in specialized environments such as disaster response and underground exploration, where their stable power supply and reliable communication offer unparalleled advantages. However, their motion planning…

机器人学 · 计算机科学 2025-07-17 Jinyuan Liu , Minglei Fu , Ling Shi , Chenguang Yang , Wenan Zhang

We present a homotopic approach to solving challenging, optimization-based motion planning problems. The approach uses Homotopy Optimization, which, unlike standard continuation methods for solving homotopy problems, solves a sequence of…

机器人学 · 计算机科学 2024-08-23 Shayan Pardis , Matthew Chignoli , Sangbae Kim

This paper presents a method for planning a trajectory in workspace coordinates using a spatially fixed tool center point (TCP), while taking into account the processing path on a part. This approach is beneficial if it is easier to move…

机器人学 · 计算机科学 2025-10-24 Bernhard Rameder , Hubert Gattringer , Andreas Mueller , Ronald Naderer

We present a centralized algorithmic framework for solving multi-robot path planning problems in general, two-dimensional, continuous environments while minimizing globally the task completion time. The framework obtains high levels of…

机器人学 · 计算机科学 2015-07-14 Jingjin Yu , Daniela Rus

This paper deals with the problem of time-constrained navigation of a robot modeled by uncertain nonlinear non-affine dynamics in a bounded workspace of $\mathbb{R}^n$. Initially, we provide a novel class of robust feedback controllers that…

系统与控制 · 计算机科学 2019-09-04 Alexandros Nikou , Dimos V. Dimarogonas

This paper presents a novel method for efficiently solving a trajectory planning problem for swarm robotics in cluttered environments. Recent research has demonstrated high success rates in real-time local trajectory planning for swarm…

机器人学 · 计算机科学 2023-11-08 Pengda Mao , Rao Fu , Quan Quan
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