3DPTG-based Reactive Navigation


3D PTG-based Reactive Navigation

Traditionally, due to the lack of affordable 3D sensors and the limited computational resources available, reactive navigators have relied on two strong assumptions:

  • The world is considered two-dimensional. Since robots usually move on a flat surface, the third dimension (height) is ignored.
  • The robot shape is simplified by a polygon or a circle projected onto the 2D world.



These two simplifications force the reactive algorithm to adopt the worst-case scenario, that is, to work with the most restrictive section of the robot and the nearest obstacle detected in each direction. This limitation can complicate or even impede many robotic platforms from carrying their tasks out. However, with the recent emergence of 3D range cameras and the current computational resources on board of robots, these assumptions are no longer justified.

In order to overcome this limitation, we propose a reactive navigator that regards both the 3D shape of the robot and the 3D geometry of the environment. Within this approach, which represents a 3D (or actually 2.5D) generalization of the PTG-based reactive navigator, the robot volume is now modeled by a number of consecutive prisms in height and the detected obstacles are sorted in corresponding height bands. Therefore, as an initial step, we decompose the 3D reactive navigator into N 2D navigators, being N the number of height sections that are used to model the robot geometry. Afterwards, these 2D navigators, which describe the navigability of each robot section in the 3D environment, are consistently and efficiently merged to yield an overall solution.

This work has been extensively tested in varied and challenging scenarios for more than 2 years. Three different robotic platforms were used to test it and are currently working with it to perform higher level tasks. A large amount of experiments were carried out to demonstrate its robustness and its advantages respect to the 2D approach.



The code is available online within the MRPT: 3D Reactive Navigation App



Please refer to the following articles for further details:

Remote Optimal, Adaptive Control of Mobile Robots with Non-Deterministic Components