Probabilistic constraint tightening techniques for trajectory planning with predictive control

Probabilistic Planning with Constraint Satisfaction techniques

Our research’s aim is to explore the use of constraint satisfaction techniques in probabilistic planning. We first focus on two special cases that make different assumptions on the observability of the domain: the conformant probabilistic planning problem (CfPP), where the agent’s environment is not observable, and the contingent probabilistic planning problem (CtPP), where the environment is f...

Application of the Model Predictive Control with Constraint Tightening for ATO System

This paper addresses an optimal train trajectory planning and tracking problem for automatic train operation (ATO) with consideration of the train model uncertainty and constraints. Based on the discrete linear multi-points train model, an ATO control algorithm is presented to track piecewise reference by using model predictive control with constraints tightening such that the feasibility and r...

Trajectory Planning Using High Order Polynomials under Acceleration Constraint

The trajectory planning, which is known as a movement from starting to end point by satisfying the constraints along the path is an essential part of robot motion planning. A common way to create trajectories is to deal with polynomials which have independent coefficients. This paper presents a trajectory formulation as well as a procedure to arrange the suitable trajectories for applications. ...

Probabilistic Techniques for Constraint Satisfaction Problems

trajectory planning using high order polynomials under acceleration constraint

the trajectory planning, which is known as a movement from starting to end point by satisfying the constraints along the path is an essential part of robot motion planning. a common way to create trajectories is to deal with polynomials which have independent coefficients. this paper presents a trajectory formulation as well as a procedure to arrange the suitable trajectories for applications. ...