Nonlinear model predictive control for wheeled mobile robot in dynamic environment

Abstract

This paper address the set-point regulation problem of a nonholonomic wheeled mobile robot with obstacle avoidance in a known dynamic environment populated with static and moving obstacles subject to robot kinematic and dynamic constraints by using the nonlinear model predictive control in polar coordinate. The terminal state penalty, terminal state constraints, and the input saturation constraints are taken into consideration in this optimization problem to guarantee the closed-loop regulation performance and stability. Simulation results are shown for illustrating the effectiveness of the control algorithm in steering a nonholonomic wheeled mobile robot.

The obstacle avoidance motion planning problem for autonomous vehicles: A low-demanding receding horizon control scheme

“…In this contribution, this difficulty is attacked by considering a very large sensing range that allows to have available sufficient time for solving the underline constrained optimization problem. Along similar lines is also [17] and the references therein. More relevant for our purposes, although limited to a single static obstacle configuration, are instead the developments of [18], where algorithms for the computation of the set of states that can be robustly steered in a finite number of steps via state feedback control to a given target set while avoiding pre-specified zones or obstacles are achieved by exploiting polyhedral algebra concepts.…”

“…The consequence of all the above developments is that the set sequences must be computed by using the following scheme: (17).…”

“…Step 13 the computation of the current command input u(t) is achieved without imposing the one-step constraint (17) as done in Step 14. In fact, note that if the robot state measurement belongs to the current obstacle scenario sc(t) collisions do not occur, therefore the requirement (17) becomes useless.…”

“…Moving from this analysis, we are here interested to consider constrained Receding Horizon Control schemes which are an extremely appealing methodology for dealing with the obstacle avoidance motion planning problem in virtue of their intrinsic capability to generate at each time instant feasible trajectories that allow to safely reach a given goal, see to cite a few the recent contributions [15][16][17][18]. In [15] the dynamic window approach (DWA) navigation scheme is recast within a continuous time nonlinear model control predictive (MPC) framework by resorting to the ideas developed in [19].…”

Efficient path planning with limit cycle avoidance for mobile robot navigation

“…Use of polar coordinate in mobile robot navigation offers some advantages in kinematic control of unicycle mobile robot [30], [31], where the distance and direction of the obstacles to the current robot position or goal are explicitly described along with some indication of their size. In view of limited energy and memory in a typical autonomous robotic system for a long distance of travel and a long time of operation in an environment whose size and structural characteristics such as obstacle geometry (convexity and concavity) and distribution are unknown, using polar coordinate system is more suitable for navigation task.…”