Obstacle Avoidance for Wheeled Robots in Unknown Environments Using Model Predictive Control
نویسندگان
چکیده
This paper presents a model predictive approach for obstacle avoidance of carlike unmanned ground vehicles (UGVs). An optimal tracking problem while avoiding obstacles in unknown environments is formulated in terms of cost minimization under constraints. Information on obstacles can be incorporated online in the nonlinear model predictive framework and kinematic constraints are treated by Karush-Kuhn-Tucker (KKT) condition. The overall problem is solved real-time with nonlinear programming. This approach is applied to car-like robots including tire models while explicitly considering the dimension of the UGV rather than treating it as a dimensionless cart model. Two kinds of potential-like terms are employed in the cost function for obstacles avoidance. The first term is to consider the distance between the UGV and the obstacle, and the second one is to consider the parallax information of the UGV about the obstacles. Simulation results show that both two approaches can make safe steering in a simple environment, but in a complex environment such as an urban area, the approach based on the modified parallax (MP) was more successful in the view of the computation time and safe steering.
منابع مشابه
Edge-weighted consensus-based formation control strategy with collision avoidance
In this paper, a consensus-based control strategy is presented to gather formation for a group of differential-wheeled robots. The formation shape and the avoidance of collisions between robots are obtained by exploiting the properties of weighted graphs. Since mobile robots are supposed to move in unknown environments, the presented approach to multi-robot coordination has been extended in ord...
متن کاملReceding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths
As mobile robots venture into more complex environments, more arbitrary feasible state-space trajectories and paths are required to move safely and efficiently. The capacity to effectively navigate such paths in the face of disturbances and changes in mobility can mean the difference between mission failure and success. This paper describes a technique for model predictive control of a mobile r...
متن کاملSensor-Based Intelligent Mobile Robot Navigation in Unknown Environments
Abstract – This paper presents sensor-based intelligent mobile robot navigation in unknown environments. The paper deals with fuzzy control of autonomous mobile robot motion in an unknown environment with obstacles and gives a wireless sensor-based remote control of mobile robots motion in an unknown environment with obstacles using the Sun SPOT technology. Simulation results show the effective...
متن کاملAutonomous Wheeled Mobile Robot Control
The autonomous wheeled mobile robots are very interesting subject both in scientific research and practical applications. The article deals with the fuzzy control of autonomous wheeled mobile robotic platform motion in an unstructured environment with obstacles. The simulation results show the effectiveness and the validity of the obstacle avoidance behaviour in unstructured environments and th...
متن کاملMethods for Collision-Free Navigation of Multiple Mobile Robots in Unknown Cluttered Environments
Navigation and guidance of autonomous vehicles is a fundamental problem in robotics, which has attracted intensive research in recent decades. This report is mainly concerned with provable collision avoidance of multiple autonomous vehicles operating in unknown cluttered environments, using reactive decentralized navigation laws, where obstacle information is supplied by some sensor system. Rec...
متن کامل