论文标题
通过CGAN的潜在空间中的无碰撞路径计划
Collision-free Path Planning in the Latent Space through cGANs
论文作者
论文摘要
我们通过将其潜在空间绘制到机器人关节空间的无碰撞区域，展示了一种新方法，用于CGAN的无碰撞路径计划。我们的方法只是提供此无碰撞潜在空间，然后任何使用任何优化条件的计划者都可以使用任何计划器来生成最合适的路径。我们通过模拟的两连锁机器人组成功验证了此方法。
We show a new method for collision-free path planning by cGANs by mapping its latent space to only the collision-free areas of the robot joint space. Our method simply provides this collision-free latent space after which any planner, using any optimization conditions, can be used to generate the most suitable paths on the fly. We successfully verified this method with a simulated two-link robot arm.
