Improving the Mobile Robot Control in Unknown Environments

Abstract – This paper gives the fuzzy reactive control of a wheeled mobile robot motion in an unknown environment with obstacles. The model of the vehicle has two driving wheels and the angular velocities of the two wheels are independently controlled. When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. We proposed a fuzzy reactive navigation strategy of collision-free motion in an unknown environment with obstacles. First, the vehicle kinematics constraints and kinematics model are analyzed. Then the fuzzy reactive control of a wheeled mobile robot motion in an unknown environment with obstacles is proposed. Output of the fuzzy controller are the angular speed difference between the left and right wheels of the vehicle and the vehicle velocity. The simulation results show the effectiveness and the validity of the obstacle avoidance behavior in an unknown environment of the proposed fuzzy control strategy.

velocities of the two wheels are independently controlled. The center of the driving wheels is regarded as the gravity center. This model is the simplest and the most suitable for the small-sized and light, battery-driven autonomous vehicle.

First, the vehicle kinematics constraints and kinematics model are analyzed. Then the fuzzy reactive control of a wheeled mobile robot motion in an unknown environment with obstacles is proposed. Output of the fuzzy controller are the angular speed difference between the left and right wheels of the vehicle and the vehicle velocity [1], [2]. Finally, the simulation results show the effectiveness and the validity of the obstacle avoidance behavior in an unknown environment of the proposed fuzzy control strategy.

FUZZY CONTROL OF A MOBILE ROBOT MOTION IN AN UNKNOWN ENVIRONMENT WITH OBSTACLES

In this section fuzzy control is applied to the navigation of the autonomous mobile robot in an unknown environment with obstacles [1], [2]. We supposed that:
the autonomous mobile robot has two wheels driven
independently and
groups of ultrasonic sensors to detect obstacles in the
front, to the right and to the left of the vehicle.

The reactive strategies are based on ultrasonic sensory information and only the relative interactions between the mobile robot and the unknown environment have to be assessed. In this case, a structural modeling of the environment is unnecessary.

When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. While the mobile robot is moving it is important to compromise between avoiding the obstacles and moving towards the target position. With obstacles present in the unknown environment, the mobile robot reacts based on both the sensed information of the obstacles and the relative position of the target (Fig. 2) [4].

Output of the fuzzy controller is the angular speed difference between the left and right wheels (wheel angular speed correction) of the vehicle: Δω= ωr – ωl.

The obstacle orientation θ1 and the target orientation θ2 are determined by the obstacle/target position and the robot position in a world coordinate system, respectively. The obstacle orientation θ1 and the target orientation θ2 are defined as positive when the obstacle/target is located to the right of the robot moving direction; otherwise, the obstacle orientation θ1 and the target orientation θ2 are negative [1]. For the proposed fuzzy controller the input variables for the obstacle distances p are simply expressed using two linguistic labels near and far (p Є [0, 3 m]). Fig. 3 shows the suitable Gaussian membership functions.

The paper deals with the modeling and control strategies of the motion of wheeled mobile robots. The model of the vehicle has two driving wheels and the angular velocities of the two wheels are independently controlled. First, the vehicle kinematics constraints and kinematics model are analyzed. Second, fuzzy reactive control of a mobile robot motion in an unknown environment with obstacles is proposed. When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. We proposed fuzzy reactive navigation strategy of collision-free motion in an unknown environment with obstacles. Output of the fuzzy controller are the angular speed difference between the left and right wheels of the vehicle and the vehicle velocity. Finally, the mobile robot simulation is illustrated. The implemented controller is computationally simple. The fuzzy reactive controller is powerful in view of the short reaction time and rapid decision-making of the obstacle avoidance process. The simulation results show the effectiveness and the validity of the obstacle avoidance behavior in an unknown environment of the proposed fuzzy control strategy.

FUZZY CONTROL OF A MOBILE ROBOT MOTION IN AN UNKNOWN ENVIRONMENT WITH OBSTACLES

In this section fuzzy control is applied to the navigation of the autonomous mobile robot in an unknown environment with obstacles [1], [2]. We supposed that:
the autonomous mobile robot has two wheels driven
independently and
groups of ultrasonic sensors to detect obstacles in the
front, to the right and to the left of the vehicle.

The reactive strategies are based on ultrasonic sensory information and only the relative interactions between the mobile robot and the unknown environment have to be assessed. In this case, a structural modeling of the environment is unnecessary.

When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. While the mobile robot is moving it is important to compromise between avoiding the obstacles and moving towards the target position. With obstacles present in the unknown environment, the mobile robot reacts based on both the sensed information of the obstacles and the relative position of the target (Fig. 2) [4].

Output of the fuzzy controller is the angular speed difference between the left and right wheels (wheel angular speed correction) of the vehicle: Δω= ωr – ωl.

The obstacle orientation θ1 and the target orientation θ2 are determined by the obstacle/target position and the robot position in a world coordinate system, respectively. The obstacle orientation θ1 and the target orientation θ2 are defined as positive when the obstacle/target is located to the right of the robot moving direction; otherwise, the obstacle orientation θ1 and the target orientation θ2 are negative [1]. For the proposed fuzzy controller the input variables for the obstacle distances p are simply expressed using two linguistic labels near and far (p Є [0, 3 m]). Fig. 3 shows the suitable Gaussian membership functions.

The paper deals with the modeling and control strategies of the motion of wheeled mobile robots. The model of the vehicle has two driving wheels and the angular velocities of the two wheels are independently controlled. First, the vehicle kinematics constraints and kinematics model are analyzed. Second, fuzzy reactive control of a mobile robot motion in an unknown environment with obstacles is proposed. When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. We proposed fuzzy reactive navigation strategy of collision-free motion in an unknown environment with obstacles. Output of the fuzzy controller are the angular speed difference between the left and right wheels of the vehicle and the vehicle velocity. Finally, the mobile robot simulation is illustrated. The implemented controller is computationally simple. The fuzzy reactive controller is powerful in view of the short reaction time and rapid decision-making of the obstacle avoidance process. The simulation results show the effectiveness and the validity of the obstacle avoidance behavior in an unknown environment of the proposed fuzzy control strategy.

REFERENCES

[1] W.L. Xu, S.K. Tso, Y.H. Fung, “Fuzzy reactive control of a mobile robot incorporating a real/virtual target switching strategy”, Robotics and Autonomous Systems, Vol. 23, pp. 171-186, 1998.
[2] Ranajit Chatterjee, Fumitoshi Matsuno, “Use of single side reflex for autonomous navigation of mobile robots in unknown environments”, Robotics and Autonomous Systems, Vol. 35, pp. 77–96, 2001.
[3] Jian Wanga, Xiangyang Zhub, Masahiro Oyac, Chun-Yi Sud, “Robust motion tracking control of partially nonholonomic mechanical systems”, Robotics and Autonomous Systems, Vol. 35 , pp. 332–341, 2006.
[4] Dragan Saletic, Uros Popovic, “Fuzzy expert system for automatic movement control of a platform on a ground with obstacles”, Proceedings of the YuINFO 2006, pp. 1-6, Kopaonik, Serbia, 2006.
[5] Jian Wanga, Xiangyang Zhub, Masahiro Oyac, Chun-Yi Sud, “Robust motion tracking control of partially nonholonomic mechanical systems”, Robotics and Autonomous Systems, Vol. 35 , pp. 332–341, 2006.
[6] Gyula Mester, “Introduction to Control of Mobile Robots”, Proceedings of the YuINFO 2006, pp. 1-4, Kopaonik, Serbia, 2006.
[7] Gyula Mester, “Modeling the Control Strategies of Wheeled Mobile Robots”, Proceedings of the Kandó Konferencia 2006, pp. 1-4, Budapest, Hungary, 2006.
[8] Gyula Mester: „Intelligent Mobile Robot Controller Design”, Proceedings of the Intelligent Engineering Systems”, INES 2006, pp. 282-286, London, United Kingdom, 2006.
[9] Gyula Mester: „Motion Control of Wheeled Mobile Robots”. Proceedings of the SISY 2006, pp. 119-130, Subotica, Serbia, 2006.
[10] János Gyeviki and Attila Csiszár, “DSP Based Positioning in Practice”, Proceeding of the 6thInternational Carpatian Control Conference, ICCC’2005, vol. I, pp. 407-412, Miskolc- Lillafüred, Hungary, 2005.
[11] István Matijevics, “Autonom rendszerek architektúrája”, in Proceedings of the Kandó Konferencia 2006, pp. 4-6, Budapest, Hungary, 2006.