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

研究问题：移动机器人的局部轨迹规划算法的计算效率能否在不影响生成轨迹的安全性、可行性或最佳性的情况下得到提高？动机：移动机器人正被用于执行各种行业的任务，包括建筑、农业、太空探索、采矿、搜救和物流。由于无线通信的带宽有限和采用其他通信方式的不切实际，移动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，这会限制可用的计算能力。因此，对于计算资源有限的车载操作，提高机器人导航过程的计算效率是可取的。目的：本研究的目的是开发一种用于移动机器人的局部轨迹规划器，其在不影响所生成轨迹的最优性、安全性或可行性的情况下，提高最新的计算效率。这是一个对时间高度敏感的领域，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。

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.