Mobile Robot Obstacle Avoidance Based on Quasi-Holonomic Smooth Paths.

The paper explores the benefits of using continuous curvature 2D paths in obstacle avoidance methods in terms of safety and comfort. To this end the paper proposes a novel contribution by introducing clothoid-based smooth paths for non-holonomic robots defined from Cartesian (x,y) and angular velocities, as if they were intended to be applied to holonomic robots. To remark, these paths, coined as quasi-holonomic continuous curvature paths (QHCC), generate purely non-holonomic motions (combinations of linear and angular velocities) that mimic a holonomic motion. In fact, QHCC paths converge to the same asymptotic direction pointed by the holonomic motion while taking into account kinematic and dynamic constraints. In the paper, we show how these paths can be used and integrated in well-known obstacle avoidance algorithms such as Nearness Diagram (ND) and Dynamic Window Approach (DWA), among others. In addition to this, an ANN has been trained to considerably speed-up the path generation process and to learn the intrinsics of the path. Additionally, the paper shows the advantages of the proposed method over standard obstacle avoidance algorithms.