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Planning in environments with moving obstacles remains a significant challenge in robotics. While many works focus on navigation and path planning in obstacle-dense spaces, traversing such congested regions is often avoidable by selecting…

Robotics · Computer Science 2025-06-23 Yaroslav Marchukov , Luis Montano

In recent years, the demand for customized, on-demand production has grown in the manufacturing sector. Additive Manufacturing (AM) has emerged as a promising technology to enhance customization capabilities, enabling greater flexibility,…

Robotics · Computer Science 2025-07-01 Yifei Li , Joshua A. Robbins , Guha Manogharan , Herschel C. Pangborn , Ilya Kovalenko

As the demand for mass customization increases, manufacturing systems must become more flexible and adaptable to produce personalized products efficiently. Additive manufacturing (AM) enhances production adaptability by enabling on-demand…

Robotics · Computer Science 2026-03-27 Yifei Li , Ruizhe Fu , Huihang Liu , Guha Manogharan , Feng Ju , Ilya Kovalenko

Robot path planning plays a pivotal role in enabling autonomous systems to navigate safely and efficiently in complex and uncertain environments. Despite extensive research on classical graph-based methods and sampling-based planners,…

Robotics · Computer Science 2025-11-04 Siyuan Wang , Shuyi Zhang , Zhen Tian , Yuheng Yao , Gongsen Wang , Yu Zhao

Motion planning is a crucial aspect of robot autonomy as it involves identifying a feasible motion path to a destination while taking into consideration various constraints, such as input, safety, and performance constraints, without…

Robotics · Computer Science 2023-06-14 Dengyu Zhang , Guobin Zhu , Qingrui Zhang

Construction robots have gained significant traction in recent years in research and development. However, the application of industrial robots has unique challenges. Dynamic environments, domain-specific tasks, and complex localization and…

Robotics · Computer Science 2025-01-30 Mani Amani , Reza Akhavian

Additive Manufacturing (AM) is a manufacturing paradigm that builds three-dimensional objects from a computer-aided design model by successively adding material layer by layer. AM has become very popular in the past decade due to its…

Machine Learning · Computer Science 2019-08-12 Arindam Paul , Mojtaba Mozaffar , Zijiang Yang , Wei-keng Liao , Alok Choudhary , Jian Cao , Ankit Agrawal

Active SLAM is the task of actively planning robot paths while simultaneously building a map and localizing within. Existing work has focused on planning paths with occupancy grid maps, which do not scale well and suffer from long term…

Robotics · Computer Science 2016-08-30 Beipeng Mu , Matthew Giamou , Liam Paull , Ali-akbar Agha-mohammadi , John Leonard , Jonathan How

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has…

Machine Learning · Computer Science 2024-07-26 Mohammad Karimzadeh , Deekshith Basvoju , Aleksandar Vakanski , Indrajit Charit , Fei Xu , Xinchang Zhang

Off-road environments present unique challenges for autonomous navigation due to their complex and unstructured nature. Traditional global path-planning methods, which typically aim to minimize path length and travel time, perform poorly on…

Autonomous systems, including robots and drones, face significant challenges when navigating through dynamic environments, particularly within urban settings where obstacles, fluctuating traffic, and pedestrian activity are constantly…

Robotics · Computer Science 2024-11-20 Daniel Ajeleye

Practical global path planning is critical for commercializing cleaning robots working in semi-structured environments. In the literature, global path planning methods for free space usually focus on path length and neglect the traffic rule…

Robotics · Computer Science 2025-11-18 Yong Li , Hui Cheng

Obstacle avoidance and path planning are essential for guiding unmanned ground vehicles (UGVs) through environments that are densely populated with dynamic obstacles. This paper develops a novel approach that combines tangentbased path…

Robotics · Computer Science 2025-11-12 Okan Arif Guvenkaya , Selim Ahmet Iz , Mustafa Unel

The ability to accurately quantify the performance an additively manufactured (AM) product is important for a widespread industry adoption of AM as the design is required to: (1) satisfy geometrical constraints, (2) satisfy structural…

Computational Engineering, Finance, and Science · Computer Science 2018-11-05 Erva Ulu

In this paper, we present an online method for converting an arbitrary geometric path represented by a sequence of states, generated by any planner (e.g., sampling-based planners like RRT or PRM, search-based planners like ARA*, etc.), into…

Robotics · Computer Science 2026-03-03 Nermin Covic , Bakir Lacevic

Path planning is a classic problem for autonomous robots. To ensure safe and efficient point-to-point navigation an appropriate algorithm should be chosen keeping the robot's dimensions and its classification in mind. Autonomous robots use…

Robotics · Computer Science 2023-05-01 Alka Choudhary

Path planning in dynamic environments is a fundamental challenge in intelligent transportation and robotics, where obstacles and conditions change over time, introducing uncertainty and requiring continuous adaptation. While existing…

Robotics · Computer Science 2025-11-20 Jonas De Maeyer , Hossein Yarahmadi , Moharram Challenger

This paper describes and evaluates the use of Generative Adversarial Networks (GANs) for path planning in support of smart mobility applications such as indoor and outdoor navigation applications, individualized wayfinding for people with…

Machine Learning · Computer Science 2018-04-24 Mehdi Mohammadi , Ala Al-Fuqaha , Jun-Seok Oh

Navigating an arbitrary-shaped ground robot safely in cluttered environments remains a challenging problem. The existing trajectory planners that account for the robot's physical geometry severely suffer from the intractable runtime. To…

Robotics · Computer Science 2026-01-07 Yisheng Li , Longji Yin , Yixi Cai , Jianheng Liu , Fangcheng Zhu , Mingpu Ma , Siqi Liang , Haotian Li , Fu Zhang

Autonomous navigation in dynamic environment heavily depends on the environment and its topology. Prior knowledge of the environment is not usually accurate as the environment keeps evolving in time. Since robot is continuously evaluating…

Robotics · Computer Science 2020-07-21 Xihan Ma , Honglin Sun , Enwei Xu , Song Cui , Boqun Yin , Mariam Faied
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