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On-line motion planning in unknown environments is a challenging problem as it requires (i) ensuring collision avoidance and (ii) minimizing the motion time, while continuously predicting where to go next. Previous approaches to on-line…

Robotics · Computer Science 2017-09-05 Sanjeev Sharma

In this paper, we present a fast, on-line mapping and planning solution for operation in unknown, off-road, environments. We combine obstacle detection along with a terrain gradient map to make simple and adaptable cost map. This map can be…

Robotics · Computer Science 2019-10-21 Timothy Overbye , Srikanth Saripalli

Unmanned aerial vehicle (UAV) use continues to increase, including operating beyond line of sight in unknown environments where the vehicle must autonomously generate a trajectory to safely navigate. In this article, we develop a trajectory…

Optimization and Control · Mathematics 2018-04-13 Kenan Cole , Adam Wickenheiser

Mobile robots are often tasked with repeatedly navigating through an environment whose traversability changes over time. These changes may exhibit some hidden structure, which can be learned. Many studies consider reactive algorithms for…

Robotics · Computer Science 2020-12-07 Florence Tsang , Tristan Walker , Ryan A. MacDonald , Armin Sadeghi , Stephen L. Smith

The problem of path planning in unknown environments remains a challenging problem - as the environment is gradually observed during the navigation, the underlying planner has to update the environment representation and replan, promptly…

Robotics · Computer Science 2022-07-20 Fan Yang , Chao Cao , Hongbiao Zhu , Jean Oh , Ji Zhang

In practical applications, the unpredictable movement of obstacles and the imprecise state observation of robots introduce significant uncertainties for the swarm of robots, especially in cluster environments. However, existing methods are…

Robotics · Computer Science 2024-10-18 Peng Liu , Pengming Zhu , Zhiwen Zeng , Xuekai Qiu , Yu Wang , Huimin Lu

Efficient real-time trajectory planning and control for fixed-wing unmanned aerial vehicles is challenging due to their non-holonomic nature, complex dynamics, and the additional uncertainties introduced by unknown aerodynamic effects. In…

This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to modeling and…

Robotics · Computer Science 2020-03-09 Yimeng Lu , Maryam Kamgarpour

Several task and motion planning algorithms have been proposed recently to design paths for mobile robot teams with collaborative high-level missions specified using formal languages, such as Linear Temporal Logic (LTL). However, the…

Robotics · Computer Science 2023-10-03 Samarth Kalluraya , George J. Pappas , Yiannis Kantaros

This paper describes and analyzes a reactive navigation framework for mobile robots in unknown environments. The approach does not rely on a global map and only considers the local occupancy in its robot-centered 3D grid structure. The…

Robotics · Computer Science 2021-08-24 Neşet Ünver Akmandor , Taşkın Padır

Developing robust locomotion for humanoid robots is a complex task due to the unstable nature of these robots and also to the unpredictability of the terrain. A robust locomotion planner is one of the fundamental components for generating…

Robotics · Computer Science 2019-09-17 Mohammadreza Kasaei , Nuno Lau , Artur Pereira

Quadrotors can provide services such as infrastructure inspection and search-and-rescue, which require operating autonomously in cluttered environments. Autonomy is typically achieved with receding-horizon planning, where a short plan is…

Robotics · Computer Science 2019-06-19 Shreyas Kousik , Patrick Holmes , Ramanarayan Vasudevan

In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This…

Robotics · Computer Science 2021-01-19 Fahad Islam , Oren Salzman , Aditya Agarwal , Maxim Likhachev

Deterministic methods for motion planning guarantee safety amidst uncertainty in obstacle locations by trying to restrict the robot from operating in any possible location that an obstacle could be in. Unfortunately, this can result in…

Robotics · Computer Science 2023-06-21 Jinsun Liu , Challen Enninful Adu , Lucas Lymburner , Vishrut Kaushik , Lena Trang , Ram Vasudevan

If we give a robot the task of moving an object from its current position to another location in an unknown environment, the robot must explore the map, identify all types of obstacles, and then determine the best route to complete the…

Robotics · Computer Science 2022-08-22 Saeid Alirezazadeh , Luís A. Alexandre

Robotic systems, particularly in demanding environments like narrow corridors or disaster zones, often grapple with imperfect state estimation. Addressing this challenge requires a trajectory plan that not only navigates these restrictive…

Robotics · Computer Science 2023-09-19 Zhenyang Chen , Hongzhe Yu , Yongxin Chen

Mobile robots are ubiquitous. Such vehicles benefit from well-designed and calibrated control algorithms ensuring their task execution under precise uncertainty bounds. Yet, in tasks involving humans in the loop, such as elderly or mobility…

Robotics · Computer Science 2023-12-08 Cristian Axenie , Matteo Saveriano

Achieving persistent tracking of multiple dynamic targets over a large spatial area poses significant challenges for a single-robot system with constrained sensing capabilities. As the robot moves to track different targets, the ones…

Robotics · Computer Science 2025-10-22 Junbin Yuan , Brady Moon , Muqing Cao , Sebastian Scherer

Designing provably safe control is a core problem in trustworthy autonomy. However, most prior work in this regard assumes either that the system dynamics are known or deterministic, or that the state and action space are finite,…

Robotics · Computer Science 2026-02-04 Xinhang Ma , Junlin Wu , Yiannis Kantaros , Yevgeniy Vorobeychik

We describe a task and motion planning architecture for highly dynamic systems that combines a domain-independent sampling-based deliberative planning algorithm with a global reactive planner. We leverage the recent development of a…