We present a novel approach for collision-free global navigation for continuous-time multi-agent systems with general linear dynamics. Our approach is general and can be used to perform collision-free navigation in 2D and 3D workspaces with narrow passages and crowded regions. As part of pre-computation, we compute multiple bridges in the narrow or tight regions in the workspace using kinodynamic RRT algorithms. Our bridge has certain geometric characteristics, that en- able us to calculate a collision-free trajectory for each agent using simple interpolation at runtime. Moreover, we combine interpolated bridge trajectories with local multi-agent navigation algorithms to compute global collision-free paths for each agent. The overall approach combines the performance benefits of coupled multi-agent algorithms with the pre- computed trajectories of the bridges to handle challenging scenarios. In practice, our approach can handle tens to hundreds of agents in real-time on a single CPU core in 2D and 3D workspaces.
The simplest solution to the difficulty of inevitable collision states is to design suitable protocols for multi-robot coordination interaction @cite_20 @cite_12 . Some other approaches precompute roadmaps or corridors in the entire workspace to achieve high-quality path planning @cite_10 @cite_24 . However, these methods are not complete and may provide sub-optimal trajectories. Our method also leverages pre-computed bridges to deal with the navigation challenges in narrow or crowded regions. However, the bridges used in our approach have special properties beneficial for efficient global navigation in challenging areas in the workspace.
@cite_24 @cite_10 @cite_12 @cite_20
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The motion-planning problem, involving the computation of a collision-free path for a moving entity amidst obstacles, is a central problem in fields such robotics and game design. In this paper we study the problem of planning high-quality paths. A high-quality path should have some desirable properties: it should be short, avoiding long detours, and at the same time it should stay at a safe distance from the obstacles, namely it should have clearance. We suggest a quality measure for paths, which balances between the above criteria of minimizing the path length while maximizing its clearance. We analyze the properties of optimal paths according to our measure, and devise an approximation algorithm to compute near-optimal paths amidst polygonal obstacles in the plane. We also apply our quality measure to corridors. Instead of planning a one-dimensional motion path for a moving entity, it is often more convenient to let the entity move in a corridor, where the exact motion path is determined by a local pla... The MARTHA project objectives are the control and the management of a fleet of autonomous mobile robots for transshipment tasks in harbors, airports and marshalling yards. One of the most challenging and key problems of the MARTHA project is multi-robot cooperation. A general concept for the control of a large fleet of autonomous mobile robots has been developed, implemented and validated in the framework of the MARTHA project. This is the first study in the autonomous mobile robot field to add multi-robot cooperation capabilities to such a large fleet of robots. Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.