Convex Optimization for Wheeled Autonomous Mobile Robots Motion Planning Applications

Abstract

Wheeled Autonomous Mobile Robots are currently the recipient of most attention in the major robotics developmental research institutes due to their wide range of applications in today’s cunning edge technology. These applications include but are not limited to space exploration, underwater navigation, search and rescue missions, intelligent transportation systems, robot racing competitions as well as agriculture and forestry robots. More common applications are industrial, manufacturing and construction robotics, but all these examples rely on a solid motion planning algorithm to ensure the wheeled robot achieves the given task without collision. Motion planning includes both trajectory planning and velocity control; this needs to be done simultaneously during the task without pre-planning as most of the applications involve an unknown environment which was not previously explored. Thus one can begin to realize the potential application of convex optimization, due to the availability of fast state of the art optimization algorithms, in order to optimize the trade-off between these two objectives, that is, if the problem can be convexified.