论文标题
部分可观测时空混沌系统的无模型预测
Stronger Together: Air-Ground Robotic Collaboration Using Semantics
论文作者
论文摘要
在这项工作中，我们提出了一个端到端的异质多机器人系统框架，地面机器人能够在高空四极管实时创建的语义图中进行本地化，计划和导航。地面机器人在没有任何外部干预的情况下独立选择并解散目标。此外，他们通过使用语义将其本地地图与架空图匹配，执行跨视图本地化。通信主链是机会主义的，并且可以分布，从而使整个系统都可以在不适合四型四次的GPS之外进行外部基础架构。我们通过在不同环境中的多个实验上执行不同的任务，通过执行不同的任务来广泛测试我们的系统。我们的地面机器人在现实世界中的干预最少，在没有干预的情况下进行了96公里以上的干预，自主行驶了超过6公里。
In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real time by a high-altitude quadrotor. The ground robots choose and deconflict their targets independently, without any external intervention. Moreover, they perform cross-view localization by matching their local maps with the overhead map using semantics. The communication backbone is opportunistic and distributed, allowing the entire system to operate with no external infrastructure aside from GPS for the quadrotor. We extensively tested our system by performing different missions on top of our framework over multiple experiments in different environments. Our ground robots travelled over 6 km autonomously with minimal intervention in the real world and over 96 km in simulation without interventions.
