避障
机器人
弹道
运动规划
计算机科学
轨迹优化
控制理论(社会学)
移动机器人
运动学
模型预测控制
路径(计算)
领域(数学)
避碰
控制工程
机器人控制
最优控制
人工智能
控制(管理)
数学优化
工程类
数学
碰撞
经典力学
物理
计算机安全
程序设计语言
纯数学
天文
作者
Christoph Rösmann,Frank Hoffmann,Torsten Bertram
标识
DOI:10.1109/iros.2017.8206458
摘要
This paper presents a novel generic formulation of Timed-Elastic-Bands for efficient online motion planning of car-like robots. The planning problem is defined in terms of a finite-dimensional and sparse optimization problem subject to the robots kinodynamic constraints and obstacle avoidance. Control actions are implicitly included in the optimized trajectory. Reliable navigation in dynamic environments is accomplished by augmenting the inner optimization loop with state feedback. The predictive control scheme is real-time capable and responds to obstacles within the robot's perceptual field. Navigation in large and complex environments is achieved in a pure pursuit fashion by requesting intermediate goals from a global planner. Requirements on the initial global path are fairly mild, compliance with the robot kinematics is not required. A comparative analysis with Reeds and Shepp curves and investigation of prototypical car maneuvers illustrate the advantages of the approach.
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