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Rapid Local Trajectory Planning for Fast-moving Autonomous Ground Vehicles in Unknown Environments

未知环境中快速移动自主地面车辆的快速局部轨迹规划

基本信息

批准号：
2902603
负责人：
金额：
--
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2902603
关键词：
Rapid Local Trajectory Planning Fast

项目摘要

Research question: Can the computational efficiency of local trajectory planning algorithms for mobile robots be improved without compromising the safety, feasibility, or optimality of the generated trajectories?Motivation: Mobile robots are being adopted to carry out a wide variety of tasks across industries including construction, agriculture, space exploration, mining, search and rescue, and logistics. Dueto the limited bandwidth of wireless communication and the impracticality of employing atether, it is desirable for mobile robots to perform computations relevant to their task usingon-board resources. However, this introduces a limit on the amount of computational poweravailable. Therefore, improving the computational efficiency of the robot navigation processes is desirable for on-board operation with limited computational resources.Aim: The aim of this research is to develop a local trajectory planner for mobile robots that improves on the computational efficiency of the state-of-the-art without compromising the optimality, safety, or feasibility of the generated trajectories.Proposed Application: This work will focus on the aggressive driving made possible by computationally efficient trajectory generation, and disaster response is a key area of application. It is a highly time-critical field, and robots must often operate in environments with widely varying levels of disruption to communicationInfrastructure.

研究问题：移动的机器人的局部轨迹规划算法的计算效率是否可以在不影响生成轨迹的安全性、可行性或最优性的情况下得到提高？动机：移动的机器人正被用于执行各种各样的任务，包括建筑、农业、太空探索、采矿、搜索和救援以及物流。由于无线通信的带宽有限以及使用无线通信的不切实际性，移动的机器人需要利用车载资源来执行与其任务相关的计算。然而，这引入了对可用计算能力的限制。因此，提高机器人导航过程的计算效率对于计算资源有限的车载操作是理想的。目的：本研究的目的是为移动的机器人开发一种局部轨迹规划器，该规划器在不影响生成轨迹的最优性、安全性或可行性的情况下，提高了现有技术的计算效率。这项工作将侧重于通过计算效率高的轨迹生成实现的积极驾驶，灾害响应是一个关键的应用领域。这是一个对时间要求很高的领域，机器人必须经常在通信基础设施中断程度差异很大的环境中运行。