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Optimizing Robotic Car Storage Service: A Stanley Robotics Case Study
技术
- 机器人 - 自动导引车 (AGV)
- 传感器 - 自动驾驶传感器
适用行业
- 汽车
- 运输
适用功能
- 物流运输
- 维护
用例
- 自主机器人
- 数字孪生
挑战
Stanley Robotics 是一家高科技公司，旨在通过引入自主机器人来移动仓库中的汽车，从而彻底改变汽车物流行业。我们面临的挑战是开发一种快速、可靠且高效的机器人，以满足汽车物流行业的需求。机器人的设计需要考虑机械优化，才能与传统汽车物流公司有效竞争。 Stanley Robotics 需要证明其机器人车辆每年可以完成大量移动并证明其耐用性。为了实现这一目标，该公司需要一个合作伙伴来帮助开发机器人的数字孪生，以计算对其提出的所有要求，并通过耐用性计算来验证其产品。
关于客户
Stanley Robotics 是一家深度科技公司，由 Clement Boussard 和 Aurélien Cord 于 2015 年创立。该公司最初的想法是通过智能机器人移动汽车，而不是使汽车自动化并赋予其自行停车的能力。在分析了机场长时间停车市场后，Stanley Robotics 意识到其产品非常适合汽车物流行业。他们的户外机器人可以在管理车队、汽车和停车活动的中央智能中心的帮助下移动重达 2600 公斤的汽车并将其存放到停车位。
解决方案
Stanley Robotics 与工程仿真软件供应商 Altair 合作。他们使用 Altair 的 Inspire Motion 使机器人多体模型能够用于预先调整尺寸。该模型通过 Altair 的 MotionSolve 得到进一步增强，可实现高级功能，包括执行 3D 道路定义、纵向和横向轮胎力（以模拟操控性和耐久性）以及专用模拟场景。斯坦利团队通过将关键部件表示为柔性体来改进模型，以捕获机器人底盘在暴露于标准化车辆耐久性事件时的变形和振动。有了完整的 CAE 流程，就可以研究机器人的灵敏度和鲁棒性，并确定最佳设计特性。
运营影响
数量效益
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