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As collaborative robots move closer to human environments, motion generation and reactive planning strategies that allow for elaborate task execution with minimal easy-to-implement guidance whilst coping with changes in the environment is…

Trajectory planning is crucial in multi-robot systems, particularly in environments with numerous obstacles. While extensive research has been conducted in this field, the challenge of coordinating multiple robots to flow collectively from…

机器人学 · 计算机科学 2026-02-03 Han Liu , Yu Jin , Mingyue Cui , Boyang Li , Tianjiang Hu , Kai Huang

Automated Guided Vehicles (AGVs) are essential in various industries for their efficiency and adaptability. However, planning trajectories for AGVs in obstacle-dense, unstructured environments presents significant challenges due to the…

机器人学 · 计算机科学 2024-03-13 Shaoqiang Liang , Songyuan Fa , Yiqun Li

This paper presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based receding-horizon approach computes a local…

机器人学 · 计算机科学 2020-10-21 Bruno Brito , Boaz Floor , Laura Ferranti , Javier Alonso-Mora

Avoiding obstacles in the perceived world has been the classical approach to autonomous mobile robot navigation. However, this usually leads to unnatural and inefficient motions that significantly differ from the way humans move in tight…

机器人学 · 计算机科学 2021-02-10 Maozhen Wang , Rui Luo , Aykut Ozgun Onol , Taskin Padir

Generating obstacle-free trajectories for robotic manipulators in unstructured and cluttered environments remains a significant challenge. Existing motion planning methods often require additional computational effort to generate the final…

机器人学 · 计算机科学 2025-09-23 Yongliang Wang , Hamidreza Kasaei

Several planners have been developed to compute dynamically feasible, collision-free robot paths from an initial to a goal configuration. A key assumption in these works is that the goal region is reachable; an assumption that often fails…

机器人学 · 计算机科学 2026-01-07 Samarth Kalluraya , Yiannis Kantaros

Collision avoidance in unknown obstacle-cluttered environments may not always be feasible. This paper focuses on an emerging paradigm shift in which potential collisions with the environment can be harnessed instead of being avoided…

机器人学 · 计算机科学 2020-09-07 Zhouyu Lu , Zhichao Liu , Gustavo J. Correa , Konstantinos Karydis

Advances in planetary robotics have led to wheeled robots that have beamed back invaluable science data from the surface of the Moon and Mars. However, these large wheeled robots are unable to access rugged environments such as cliffs,…

机器人学 · 计算机科学 2018-03-18 Steven Morad , Himangshu Kalita , Jekan Thangavelautham

Recent advances in trajectory replanning have enabled quadrotor to navigate autonomously in unknown environments. However, high-speed navigation still remains a significant challenge. Given very limited time, existing methods have no strong…

机器人学 · 计算机科学 2020-07-08 Boyu Zhou , Jie Pan , Fei Gao , Shaojie Shen

Ensuring safety is crucial to promote the application of robot manipulators in open workspaces. Factors such as sensor errors or unpredictable collisions make the environment full of uncertainties. In this work, we investigate these…

机器人学 · 计算机科学 2025-04-01 Xinyu Jia , Wenxin Wang , Jun Yang , Yongping Pan , Haoyong Yu

Manipulating deformable objects arises in daily life and numerous applications. Despite phenomenal advances in industrial robotics, manipulation of deformable objects remains mostly a manual task. This is because of the high number of…

机器人学 · 计算机科学 2024-01-31 Burak Aksoy , John Wen

Autonomous Underwater Vehicles (AUVs) need to operate for days without human intervention and thus must be able to do efficient and reliable task planning. Unfortunately, efficient task planning requires deliberately abstract domain models…

Socially-aware robotic navigation is essential in environments where humans and robots coexist, ensuring both safety and comfort. However, most existing approaches have been primarily developed for mobile robots, leaving a significant gap…

机器人学 · 计算机科学 2025-06-18 Caio C. G. Ribeiro , Leonardo R. D. Paes , Douglas G. Macharet

The design process and complexity of existing safety controls are heavily determined by the geometrical properties of the environment, which affects the proof of convergence, design scalability, performance robustness, and numerical…

机器人学 · 计算机科学 2021-04-30 Azad Ghaffari , Seyed Amir Hosseini Dastja

The environment of low-altitude urban airspace is complex and variable due to numerous obstacles, non-cooperative aircrafts, and birds. Unmanned aerial vehicles (UAVs) leveraging environmental information to achieve three-dimension…

系统与控制 · 电气工程与系统科学 2024-04-30 Chao Dong , Yifan Zhang , Ziye Jia , Yiyang Liao , Lei Zhang , Qihui Wu

Surgical workflow anticipation is the task of predicting the timing of relevant surgical events from live video data, which is critical in Robotic-Assisted Surgery (RAS). Accurate predictions require the use of spatial information to model…

计算机视觉与模式识别 · 计算机科学 2024-12-10 Francis Xiatian Zhang , Jingjing Deng , Robert Lieck , Hubert P. H. Shum

Safely deploying robots in uncertain and dynamic environments requires a systematic accounting of various risks, both within and across layers in an autonomy stack from perception to motion planning and control. Many widely used motion…

系统与控制 · 电气工程与系统科学 2020-02-10 Venkatraman Renganathan , Iman Shames , Tyler H. Summers

During the conceptual and prototype design stage of an industrial product, it is crucial to take assembly/disassembly and maintenance operations in advance. A well-designed system should enable relatively easy access of operating…

机器人学 · 计算机科学 2012-06-08 Liang Ma , Ruina Ma , Damien Chablat , Fouad Bennis

Traversing environments with arbitrary obstacles poses significant challenges for bipedal robots. In some cases, whole body motions may be necessary to maneuver around an obstacle, but most existing footstep planners can only select from a…

机器人学 · 计算机科学 2017-03-22 Michael X. Grey , Aaron D. Ames , C. Karen Liu
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