A real-time path planner for a smart wheelchair using harmonic potentials and a rubber band model

Abstract

We present an efficient path planner for smart wheelchairs based on harmonic potential fields. While the use of harmonic fields can always guarantee finding an existing path, they are extremely computational intensive and a sufficiently detailed map of the environment may lead to an unfeasible solution for the path. Also, since our target application is for the navigation of a smart wheelchair, for people with severe disabilities, the path provided by the harmonic field is frequently too sharp and needs to be smoothened. In order to address the first problem, we propose a parallel algorithm implemented using Graphics Processor Units (GPUs) on the Compute Unified Device Architecture (CUDA) platform. And for the second problem, we developed a rubber band model that provides extra forces to be added to the attracting forces of the harmonic fields. This model assumes that the path is an elastic line, a rubber band, connecting the source and destination points. This rubber band simulates the internal tension forces trying to tighten the line. As the result section demonstrates, both the original path from the harmonic field alone and the path smoothened by the rubber band model have approximate the same length, but the first path contains many bumps, sharp angles, and zigzags , while the second one provides a much more comfortable ride for the passenger of the wheelchair. Either one is executed in real-time, allowing the proposed method to be used for real navigation of smart wheelchairs.

Applications of parallel computing in robotics problems

“…While these consequences may be acceptable for a mobile robot, applications involving autonomous wheelchair navigation can become quite uncomfortable for human passengers. In [68], it was proposed a robust method using a rubber band model to smoothen the path and reduce the number of sharp angles obtained from the use of harmonic potential fields alone. While that approach worked well for static environments, it did not address the case of moving obstacles.…”

“…As it was pointed out earlier, the path produced by HP can present sharp turns, which for many applications, such as autonomous wheelchair navigation, can produce an uncomfortable experience for the passenger. So, we re-introduce the idea of a Rubber Band model [68] to smoothen the path created by the HP. Since moving obstacles can also lead to unexpected changes in path, we proposed the use of Kalman Filter for stochastic estimation of the positions of the obstacles.…”

“…This speed up of the algorithm allows for the values of the next iteration to quickly propagate through the grid. However, it also distorts the real value of the harmonic potentials [68].…”

“…As proposed in [68], the rubber band model is employed to optimize the path obtained by the harmonic potential fields. This idea of rubber band was previously introduced in [ by the pair (x, y) that leads to the resultant forces to be minimum.…”

“…The problem of using harmonic fields is that it requires repeated updates of the potential values at every cell of the grid. These updates are in turn a function of the potential of the neighboring cells, which leads to a recursive and quite-time consuming algorithm[68]. Furthermore, the algorithm for optimizing the path using the rubber band model needs to calculate different forces at every cells of the grid in all iterations which is a heavy process.…”