概括
这项研究提出了一种基于数据的多因素控制的新方法,提高了避免碰撞和障碍物导航. 该方法确保了安全的轨迹规划和适应性减速,以控制强大的剂量形成.
科学领域:
- 机器人技术
- 控制系统工程
- 人工智能
背景情况:
- 多代理系统在碰撞和避开障碍方面面临挑战,特别是在非线性控制场景中.
- 现有方法通常需要复杂的模型或集中控制,限制可扩展性和适应性.
- 数据驱动的方法在动态环境中提供了更灵活和更强大的解决方案.
研究的目的:
- 开发数据驱动的合作输出控制策略,以避免非线性多代理系统中的碰撞和障碍.
- 设计一个安全的参考轨迹规划方法,使操作人员能够动态绕过障碍物.
- 创建一个分布式跟踪控制器,只使用输入输出信息来进行自适应性碰撞预防.
主要方法:
- 安全参考轨道规划方法可以动态地预测不安全的轨道段,以规避障碍物.
- 一个具有两个动态屏障功能的分布式跟踪控制器是使用输入输出数据设计的.
- 有足够的条件来保证成功避开障碍物和安全航行.
主要成果:
- 建议的策略使代理人能够有效地避开静止和移动的障碍.
- 这种方法可以防止组合中的单个物质发生碰撞.
- 代理人成功地追踪所需的轨迹,同时保持阵营完整性.
结论:
- 数据驱动的合作输出方法为非线性多剂控制中避免碰撞和障碍提供了有效的解决方案.
- 拟议的轨道规划和适应性控制方法可确保安全有效的航行.
- 模拟结果验证了复杂场景中的战略的稳定性和性能.
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