A membrane computing framework for social navigation in robotics

Abstract

A mobile robot acting in a human environment should follow social conventions, keeping safety distances and navigating at moderate speeds, in order to respect people in its surroundings and avoid obstacles in real-time. The problem is more complex in differential-drive wheeled robots, with trajectories constrained by nonholonomic and kinematics restrictions. It is an NP-hard problem widely studied in the literature, combining disciplines such as Psychology, Mathematics, Computer Science and Engineering. In this work, we propose a novel solution based on Membrane Computing, Social Force Model and Dynamic Window Approach Algorithm. The resulting model is able to compute, in logarithmic time, the best motion command for the robot, given its current state, considering the surrounding people and obstacles. The model is compatible with other membrane computing models for robotics and suitable for an implementation on parallel hardware. Finally, a visual simulator was implemented in ROS and C++ for validation and testing.