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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…
This letter aims to present a novel approach for unmanned aerial vehicles (UAV)' path planning with respect to certain quality of service requirements. More specifically, we study the max-min fairness problem in an air-to-ground…
Localization in a global map is critical to success in many autonomous robot missions. This is particularly challenging for multi-robot operations in unknown and adverse environments. Here, we are concerned with providing a small unmanned…
In unstructured environments, obstacles are diverse and lack lane markings, making trajectory planning for intelligent vehicles a challenging task. Traditional trajectory planning methods typically involve multiple stages, including path…
Safe UAV navigation is challenging due to the complex environment structures, dynamic obstacles, and uncertainties from measurement noises and unpredictable moving obstacle behaviors. Although plenty of recent works achieve safe navigation…
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…
This paper investigates the problem of traffic surveillance using an unmanned aerial vehicle (UAV) and proposes a domain-knowledge-aided airborne ground moving targets tracking algorithm. To improve the accuracy of multiple targets…
Autonomous mobile robots have the potential to solve missions that are either too complex or dangerous to be accomplished by humans. In this paper, we address the design and autonomous deployment of a ground vehicle equipped with a robotic…
Autonomous ground vehicle systems have found extensive potential and practical applications in the modern world. The development of an autonomous ground vehicle poses a significant challenge, particularly in identifying the best path plan,…
We investigate the autonomous navigation of a mobile robot in the presence of other moving vehicles under time-varying uncertain environmental disturbances. We first predict the future state distributions of other vehicles to account for…
Urban environments offer a challenging scenario for autonomous driving. Globally localizing information, such as a GPS signal, can be unreliable due to signal shadowing and multipath errors. Detailed a priori maps of the environment with…
Path planning in unknown environments is a crucial yet inherently challenging capability for mobile robots, which primarily encompasses two coupled tasks: autonomous exploration and point-goal navigation. In both cases, the robot must…
In this paper, we present a learning approach to goal assignment and trajectory planning for unlabeled robots operating in 2D, obstacle-filled workspaces. More specifically, we tackle the unlabeled multi-robot motion planning problem with…
The global positioning system (GPS) has become an indispensable navigation method for field operations with unmanned surface vehicles (USVs) in marine environments. However, GPS may not always be available outdoors because it is vulnerable…
Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space. The difficulty of MRMP increases with the number of robots and is exacerbated in environments with narrow…
Multiple fixed-wing unmanned aerial vehicles (multi-UAVs) encounter significant challenges in cooperative path following over complex Digital Elevation Model (DEM) low-altitude airspace, including wind field disturbances, sudden obstacles,…
There are so many vehicles in the world and the number of vehicles is increasing rapidly. To alleviate the parking problems caused by that, the smart parking system has been developed. The parking planning is one of the most important parts…
Purpose of Review Planning collision-free paths for multiple robots is important for real-world multi-robot systems and has been studied as an optimization problem on graphs, called Multi-Agent Path Finding (MAPF). This review surveys…
Recent years have seen an increasing number of deployment of fleets of autonomous vehicles. As the problem scales up, in terms of autonomous vehicles number and complexity of their objectives, there is a growing need for decision-support…
Autonomous navigation of ground robots on uneven terrain is being considered in more and more tasks. However, uneven terrain will bring two problems to motion planning: how to assess the traversability of the terrain and how to cope with…