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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…

机器人学 · 计算机科学 2010-07-16 Stephen L. Smith , Jana Tumova , Calin Belta , Daniela Rus

Industrial robots are widely used in various manufacturing environments due to their efficiency in doing repetitive tasks such as assembly or welding. A common problem for these applications is to reach a destination without colliding with…

机器人学 · 计算机科学 2023-01-18 Teham Bhuiyan , Linh Kästner , Yifan Hu , Benno Kutschank , Jens Lambrecht

We propose a path planning methodology for a mobile robot navigating through an obstacle-filled environment to generate a reference path that is traceable with moderate sensing efforts. The desired reference path is characterized as the…

机器人学 · 计算机科学 2022-12-09 Ali Reza Pedram , Riku Funada , Takashi Tanaka

Real-time long-range local planning is a challenging task, especially in the presence of dynamics obstacles. We propose a complete system which is capable of performing the local replanning in real-time. Desired trajectory is needed in the…

机器人学 · 计算机科学 2020-11-04 Geesara Kulathunga , Roman Fedorenko , Sergey Kopylov , Alexandr Klimchik

At the heart of path-planning methods for autonomous robotic exploration is a heuristic which encourages exploring unknown regions of the environment. Such heuristics are typically computed using frontier-based or information-theoretic…

机器人学 · 计算机科学 2020-11-11 Di Deng , Runlin Duan , Jiahong Liu , Kuangjie Sheng , Kenji Shimada

This paper addresses the problem of coordination of a fleet of mobile robots - the problem of finding an optimal set of collision-free trajectories for individual robots in the fleet. Many approaches have been introduced during the last…

机器人学 · 计算机科学 2019-01-23 Jakub Hvězda , Miroslav Kulich , Libor Přeučil

We address the problem of controlling a mobile robot to explore a partially known environment. The robot's objective is the maximization of the amount of information collected about the environment. We formulate the problem as a partially…

机器人学 · 计算机科学 2017-03-08 Mikko Lauri , Risto Ritala

Sampling-based motion planners perform exceptionally well in robotic applications that operate in high-dimensional space. However, most works often constrain the planning workspace rooted at some fixed locations, do not adaptively reason on…

机器人学 · 计算机科学 2021-03-09 Tin Lai

Robots are increasingly deployed in dynamic and crowded environments, such as urban areas and shopping malls, where efficient and robust navigation is crucial. Traditional risk-based motion planning algorithms face challenges in such…

机器人学 · 计算机科学 2024-11-04 Zhirui Sun , Bingyi Xia , Peijia Xie , Xiaoxiao Li , Jiankun Wang

We present a navigation system that combines ideas from hierarchical planning and machine learning. The system uses a traditional global planner to compute optimal paths towards a goal, and a deep local trajectory planner and velocity…

Trajectory planning for mobile robots in cluttered environments remains a major challenge due to narrow passages, where conventional methods often fail or generate suboptimal paths. To address this issue, we propose the adaptive trajectory…

机器人学 · 计算机科学 2025-10-31 Hahjin Lee , Young J. Kim

In this paper, we consider a robot navigation problem in environments populated by humans. The goal is to determine collision-free and dynamically feasible trajectories that also maximize human satisfaction. This is because they may drive…

机器人学 · 计算机科学 2020-11-04 Yijie Zhou , Yan Zhang , Xusheng Luo , Michael M. Zavlanos

Robust motion planning entails computing a global motion plan that is safe under all possible uncertainty realizations, be it in the system dynamics, the robot's initial position, or with respect to external disturbances. Current approaches…

机器人学 · 计算机科学 2022-11-02 Albert Wu , Thomas Lew , Kiril Solovey , Edward Schmerling , Marco Pavone

This paper presents a novel interaction planning method that exploits impedance tuning techniques in response to environmental uncertainties and unpredictable conditions using haptic information only. The proposed algorithm plans the…

机器人学 · 计算机科学 2023-05-17 Yasuhiro Kato , Pietro Balatti , Juan M. Gandarias , Mattia Leonori , Toshiaki Tsuji , Arash Ajoudani

Autonomous exploration of unknown environments is a vital function for robots and has applications in a wide variety of scenarios. Our focus primarily lies in its application for the task of efficient coverage of unknown environments.…

机器人学 · 计算机科学 2021-08-27 Arsh Tangri , Dhruv Joshi , Ashalatha Nayak

In this paper, we consider the problem of using a robot to explore an environment with an unknown, state-dependent disturbance function while avoiding some forbidden areas. The goal of the robot is to safely collect observations of the…

机器人学 · 计算机科学 2021-05-17 Dawei Sun , Mohammad Javad Khojasteh , Shubhanshu Shekhar , Chuchu Fan

Mobile robots rely on maps to navigate through an environment. In the absence of any map, the robots must build the map online from partial observations as they move in the environment. Traditional methods build a map using only direct…

机器人学 · 计算机科学 2024-10-14 Vishnu Dutt Sharma

Autonomous robot person-following (RPF) systems are crucial for personal assistance and security but suffer from target loss due to occlusions in dynamic, unknown environments. Current methods rely on pre-built maps and assume static…

机器人学 · 计算机科学 2025-07-14 Hanjing Ye , Kuanqi Cai , Yu Zhan , Bingyi Xia , Arash Ajoudani , Hong Zhang

In this paper we propose a planner for 3D exploration that is suitable for applications using state-of-the-art 3D sensors such as lidars, which produce large point clouds with each scan. The planner is based on the detection of a frontier -…

机器人学 · 计算机科学 2021-09-15 Ana Batinović , Tamara Petrović , Antun Ivanovic , Frano Petric , Stjepan Bogdan

Robust navigation in changing marine environments requires autonomous systems capable of perceiving, reasoning, and acting under uncertainty. This study introduces a hybrid risk-aware navigation architecture that integrates probabilistic…

机器人学 · 计算机科学 2026-03-25 Ozan Kaya , Emir Cem Gezer , Roger Skjetne , Ingrid Bouwer Utne