具有安全约束的自动割草机三维地形覆盖轨迹规划问题:精确和启发式方法

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Hang Zhou, Peng Zhang, Zhaohui Liang, Hangyu Li, Xiaopeng Li
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引用次数: 0

摘要

最近自动化技术的进步引起了人们对自动割草机的兴趣。开发一个安全有效的轨迹来覆盖整个地形对于自动割草至关重要。与现有文献中通常假设的具有平坦表面的简化室内环境不同,草坪维护通常发生在以不规则地形为特征的复杂室外环境中,包括障碍物和斜坡。这些不规范构成了重大的安全风险,例如割草机翻倒的可能性。本文介绍了三维地形覆盖轨迹规划问题(CTPP-3DT),该问题涉及确定自动割草机的路径和速度轮廓,以有效覆盖具有不同坡度的一般三维地形。CTPP-3DT的目标是最小化完成时间,包括转弯时间,以满足机器人在各种斜坡上的速度和加速度的安全约束。为了解决这一挑战,我们首先提出了一种基于图展开方法的混合整数线性规划(MILP)模型,适用于求解小规模实例。对于较大的实例,我们使用模拟退火开发了基于分解的启发式算法。在基准实例上进行的大量实验证明了我们提出的MILP模型和启发式算法在小尺寸和大尺寸实例上的有效性。优化策略与保守策略的对比凸显了在轨迹规划中纳入安全约束的必要性,平均缩短了40%以上的完工时间。此外,敏感性分析表明,割草机的技术进步,如提高最大速度和加速度,降低转弯速度,可以显着缩短总体完成时间。我们的代码和数据可在https://github.com/CATS-Lab/Mower-CTPP-3D上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coverage Trajectory Planning Problem on 3D Terrains with safety constraints for automated lawn mower: Exact and heuristic approaches
Recent technological advancements in automation have attracted increased interest in automated lawn mowers. Developing a safe and efficient trajectory to cover entire terrains is crucial for autonomous mowing. Unlike the simplified indoor environments with flat surfaces commonly assumed in existing literature, lawn maintenance typically occurs in complex outdoor settings characterized by irregular terrains, including obstacles and slopes. These irregularities pose significant safety risks, such as the potential for the mower to tip over. This paper introduces the Coverage Trajectory Planning Problem on 3D Terrains (CTPP-3DT), which involves determining both the path and speed profile for an automated lawn mower to effectively cover a general 3D terrain with varying slopes. The objective of the CTPP-3DT is to minimize the completion time, including the time for turning, which satisfies safety constraints on the robot’s speed and acceleration on various slopes. To address this challenge, we first propose a Mixed-Integer Linear Programming (MILP) model based on a graph expansion method, suitable for solving small-scale instances. For larger instances, we develop a decomposition-based heuristic algorithm using Simulated Annealing. Extensive experiments conducted on benchmark instances demonstrate the effectiveness of our proposed MILP model and heuristic algorithm for small-size and large-size instances. The comparison between the optimized strategy and the conservative strategy highlights the necessity of incorporating safety constraints in trajectory planning, resulting in an average reduction of more than 40% in completion time. Furthermore, sensitivity analyses reveal that technological advancements in mowers, such as increasing the maximum speed and acceleration and reducing turning speed, can significantly reduce the overall completion time. Our code and data are available at https://github.com/CATS-Lab/Mower-CTPP-3D.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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