Predictive navigation of an autonomous vehicle with nonholonomic and minimum turning radius constraints

Abstract

A key feature of an autonomous vehicle is the ability to re-plan its motion from a starting configuration (position and orientation) to a goal configuration while avoiding obstacles. Moreover, it should react robustly to uncertainties throughout its maneuvers. We present a predictive approach for autonomous navigation that incorporates the shortest path, obstacle avoidance, and uncertainties in sensors and actuators. A car-like robot is considered as the autonomous vehicle with nonholonomic and minimum turning radius constraints. The results (arcs and line segments) from a shortest-path planner are used as a reference to find action sequence candidates. The vehicle's states and their corresponding probability distributions are predicted to determine a future reward value for each action sequence candidate. Finally, an optimal action policy is calculated by maximizing an objective function. Through simulations, the proposed method demonstrates the capability of avoiding obstacles as well as of approaching a goal. The regenerated path will incorporate uncertainty information.

Constrained control of hot air blower system under output delay using globally stable performance-based anti-windup approach

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A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding

“…There are two general methods used for localization: relative positioning and absolute positioning [1]. Relative positioning, also known as dead reckoning, evaluates the position of the mobile robot by using its velocity and yaw angles measured by encoders attached to the robot's wheels or by inertial sensors [1][2][3][4][5][6][7][8]. Absolute positioning evaluates the position of the mobile robot by using external distance measuring systems.…”

“…Generally, it uses an inertial measurement unit (IMU) or a control variable, such as an encoder, and so does not depend on external signals [1][2][3][4][5][6][7][8][9][10][11][12]. Therefore dead reckoning has advantages in being simple, low cost, and has an easier time in estimating the position in real time compared to absolute positioning.…”

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