Path Planning Using Probability Tensor Flows

Robot Path Planning Using Cellular Automata and Genetic Algorithm

In path planning Problems, a complete description of robot geometry, environments and obstacle are presented; the main goal is routing, moving from source to destination, without dealing with obstacles. Also, the existing route should be optimal. The definition of optimality in routing is the same as minimizing the route, in other words, the best possible route to reach the destination. In most...

Time and Energy Optimal Path Planning in General Flows

Autonomous surface and underwater vehicles (ASVs and AUVs) are increasingly being used for persistent monitoring of ocean phenomena. Typically, these vehicles are deployed for long periods of time and must operate with limited energy budgets. As a result, there is increased interest in recent years on developing energy efficient motion plans for these vehicles that leverage the dynamics of the ...

A probability-based approach to model-based path planning

Probability-based Optimal Path Planning for Two-wheeled Mobile Robots

Most dynamic systems show uncertainty in their behavior. Therefore, a deterministic model is not sufficient to predict the stochastic behavior of such systems. Alternatively, a stochastic model can be used for better analysis and simulation. By numerically integrating the stochastic differential equation or solving the Fokker-Planck equation, we can obtain a probability density function of the ...

Path Planning Using Lazy PRM