MOBILE ROBOT ABLE TO NAVIGATE IN AN UNSTRUCTURED ENVIRONMENT

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1 SISOM 2008 and Session of the Commission of Acoustics, Bucharest May MOBILE ROBOT ABLE TO NAVIGATE IN AN UNSTRUCTURED ENVIRONMENT Boris-Sergiu CONONOVICI, Gheorghe NIŢU Institute of Solid Mechanics of the Romanian Academy, Robotics-Mechatronics Group Corresponding author: Boris-Sergiu Cononovici, Institute of Solid Mechanics, Robotics-Mechatronics Group, 15 C-tin Mille St., Sector 1, Bucharest, Romania, fax: , This paper presents an actual mobile robot, able to navigate in an unknown environment from a start point to a goal one, avoiding encountered unpredictable obstacles. The robot structure and control are presented. The control is shared between two modules, called PILOT and NAVIGATOR, respectively. These two modules represent two layers of competence that operate parallel, changing messages between each to other to accomplish the robot tasks. Key Words: autonomous mobile robot, reactive behaviour, navigation, two-level control 1. INTRODUCTION Path planning is the most important task in the navigation of autonomous mobile robots. This may be divided in two levels: on the one hand, it is the global planning at the highest level, based on an a priori knowledge of the environment and of the goals, and on the other hand, it is a local path planning based on sensory information about environment where the locations of the obstacles are unknown. Perceptually acquired knowledge about environment is typically incomplete and affected by noise. The limitations introduced by the visual field increase the difficulties related to interpretation of the perception process, [1, 5]. The control of a mobile robot may be seen as trying to attain strategic goals and reacting to the events in the environment perceived by sensors. The autonomy involves an intelligent behaviour. The complexity of a mobile robot control brings about the need to decompose the problem in parts and, by solving the sub problems and composing the solutions, to build the solution of the main problem. Brooks, [2], proposes a number of levels of competence for an autonomous mobile robot. The problem is to build a system able to react to unforeseeable events. The elementary responses, small independent decision-making processes, are called behaviours. Each of behaviours is responsible for an action (usually motor action). The behaviours are stated by rules perception-action, which are periodically applied for the robot control. Behaviours that only use the current perceptual data, possibly after some perceptual interpretation, are called reactive. The approach in this work is based on the building of a reactive system using the information provided by infrared proximity sensors. In a reactive system, no planning mediates between perception and action. The action taken is computed immediately as a function of the current situation. A reactive system examines periodically its sensors and uses their readings in a rule base table for finding the suitable response, [1, 5]. The knowledge of a reactive system is represented as situation-action rules. The extension of mobile robot aptitudes so that it becomes able to find the path from a start position point up to a goal one, was tackled with the following premises: the robot must become able to navigate without colliding into the encountered obstacles; like in other works, the start and the goal positions are considered known; based on dead reckoning (using odometry), which allows one to find out the position and orientation of the robot, the instant direction to the goal can be obtained. Based on these, two kinds of behaviours were established: if the way up to the goal is free: move on the goal direction;

2 Boris-Sergiu Cononovici, Gheorghe Niţu 326 if an obstacle was encountered: avoid it so that a free way to the goal can be seen. The control function of the mobile robot is shared between two modules, called PILOT and NAVIGATOR, respectively, implemented on two micro controllers. The PILOT function is to perform the perception function and to ensure obstacle avoidance. The NAVIGATOR monitors the two motor wheels, performs the odometry and ensures the navigation from the start position up to the destination. 2. THE MOBILE ROBOT The considered mobile robot is composed by a chassis and a platform supplied with two driving wheels mounted in front of the chassis and a free rear wheel. The two driving wheels are independently driven by two actuators to achieve the motor function, the displacement and steering. Standard servos, modified for continuous movement, are used as actuators (figure 1): y Y θ X M 2r O x Figure 1 - The mobile robot in the environment. Because the rotation of wheels is foreseen to be in a single direction, the steering is performed keeping the wheel inside the rotation arc stopped. The position of the mobile robot in the global frame xoy can be defined by the position of the point M situated on the drivers axis like in figure 1. Point M is the origin of the frame XMY attached to the robot. The orientation is given by angle θ. α X' Y' M' X α Y M r C Figure 2 - The steering manoeuvre.

3 327 Mobile Robot Able to Navigate in an Unstructured Environment Because of the manner of steering, the rotation by an angle α involves the alteration of the position of point M in the base frame (figure 2). The position alteration in the old frame XMY is expressed by: ΔX = r sin α ΔY = r (1 - cos a) where 2r is the distance between wheels. For right hand rotation, ΔY is (-ΔY). The robot position alteration Δx and Δy in the base frame is obtained multiplying the vector [ΔX, ΔY] T by a rotation matrix H: The new angle of orientation is: Δx ΔX = y H i Δ ΔY H = Cθ Sθ Sθ Cθ θ' = θ + α (3) The sign of angle α depends on the rotation direction. With a view to perform navigation, dead reckoning must be possibly. For this aim wheel watcher encoders are attached to motor wheels in order to obtain incremental encoders. To each of the wheels an aluminium disk with 32 circular holes is mounted. This is the code wheel. A photo sensor provides pulses at each transition from hole to the aluminium reflecting surface. The motor wheels diameter of 45 mm entails a measurement step u = mm. This unit is used for position measurement during dead reckoning. The sensorial function of the robot is accomplished by 4 infrared sensors S1 to S4 placed as shown in figure 3: + 45 o (1) (2) Y + 15 o y M S 1 S2 S 3 X -15 o S 4 O x -45 o Figure 3 - Sensors exploring scheme. The perception function implements the exploring with a certain step of each sensor direction in order to get the local perception periodically. In the frame attached to the robot, the angles of free way sensor directions ϕ j are: -45 o, -15 o, +15 o, +45 o. The coordinate frames, the sensor directions and the exploring scheme are shown in figure 3. Each sensor is made of an infrared transmitter and a receiver. By measuring the reflected light by an encountered object surface, the distance till this one can be measured.

4 Boris-Sergiu Cononovici, Gheorghe Niţu 328 The infrared transmitter LED is fed with 1 ms pulses with carrier frequency 38.5 khz. This is the central frequency of the infrared detector filter, on which it is most sensitive. The filter characteristic is used for qualitative distance measurement. For frequencies that make the detector less sensitive, the object has to be closer to make the reflected infrared signal adequate to be detected. The uncertainty of distance measurement justifies the choice of qualitative estimation. The perception domain of sensors was divided in three disjoined and contiguous sub domains: close, far and out of range, 200 mm, 400 mm and more, respectively. All distances are measured in local unit u. The control of the robot is implemented on two micro controllers BS2e (Parallax) running in parallel. The programming language is PBASIC specifically developed for these micro controllers. 3.1 The reactive behaviour 3. THE CONTROL STRATEGIES The reactive system is a modular network that receives situations and computes actions. A perception function is responsible for sensor reading in order to get the perception vectors V p. Patterns of perception vectors are contained in a look-up table Numerical Coding of Perceptions - NCP. The perception vector is compared with the contents of the Numerical Coding of Perceptions and determines the cod of perception - CP. The reactive simplified function is a mapping on the perceptual states set P with values in the action set A: f r : P A (4) The rules perception-action can be expressed using conditional statements to describe a certain situation: if X is A i then Z is C j (5) where X and Z are two variables and A i and C j are qualitative, [1], or fuzzy sets over the input domain U and output domain V, respectively. This inference represents the mapping between the sensor input space U and the mobile robot action space V. The rule-based inference provides this mapping. The action function determines, at the same sampling period as perception, the motor subordinate actions. There are provided for three distinct actions: translation T r, left steering R s or right steering R d. The action R s or R d can take values [ ]. The aptitudes of the mobile robot are extended so that it becomes able to navigate from an initial location to a goal one finding the free path. At each sampling step the direction θ d to the goal is checked up. If this direction is free, a displacement by a translation step is performed, otherwise there is an obstacle. Being known the instant orientation θ of the robot in the base frame, the angle Δθ between goal direction and the robot axis is computed: Δθ = θ d - θ (6) If an obstacle was encountered, it is avoided so that the direction to the goal is free again. Perception and obstacle avoidance are the task of the PILOT module. 3.2 The navigation The navigation is performed by a module called NAVIGATOR. The database of the NAVIGATOR contains: x 0, y 0, θ 0 - the initial position and orientation; x d, y d - the position of the goal, the destination; θ d - the angle between Ox axis and the straight line that joins the robot and goal characteristic points; x, y, θ - the current position and orientation of robot.

5 329 Mobile Robot Able to Navigate in an Unstructured Environment For navigation from a start position up to a goal one, in an unstructured environment, where the straightforward way to the goal may be broken by obstacles that must be avoided, a rule is necessary to be prescribed for sampling the position and orientation of the robot. If the way seems to be free (possible obstacles are out of range of perception), the robot shifts to the goal, otherwise some manoeuvres must be performed by the PILOT to avoid the encountered obstacle. To be carried the navigation task, the position and orientation of the robot (x, y, θ) are computed after every steering or after every linear displacement by a step of 25u (~110 mm). This function is performed by a software module called Position-Orientation (PO). The input data are the readings of counters of pulses coming from the wheel watchers. The position and orientation are brought up-to-date using equations (2), (3) and: - for position where - for reorientation: x = x + Δx y = y + Δy Δθ = θ d - θ (8) θ d = ATAN2 (y d - y, x d - x) (9) The NAVIGATOR takes the control if the perception message is free way and then it guides the robot to the goal. In the neighbourhood of the goal the step is successively reduced to a half. The obstacle avoidance is performed by the PILOT, but the manoeuvres are supervised by the NAVIGATOR computing the current position and orientation. (7) 4. THE CONTROL FUNCTION As stated earlier, the control is implemented on two micro controllers running in parallel. According to Brooks, [2], two levels of competence are materialised on two layers system. Each layer is controlled by a micro controller programmed to accomplish its competence. The lower level - the PILOT, when working alone, is able to avoid obstacles and to wander aimlessly. With that end in view, it performs the perception function periodically at a sampling of 100 ms. For displacement and steering for obstacle avoidance, the PILOT module takes the control of the motor function. The second layer, the higher level, is the NAVIGATOR, which adds additional competence to the robot. Counting the pulses from the wheel watcher permanently, the Position and Orientation program, implemented on the micro controller of this layer, performs the dead reckoning. The position and orientation are activated by the message transition during the PILOT control and internally during navigation. If the free way state is perceived by the PILOT, it sends a message to the NAVIGATOR, which takes the robot control to pilot it to the goal. With that end in view, the NAVIGATOR module sends messages to the PILOT for wheels actuators. The NAVIGATOR module takes the motor function control. The NAVIGATOR task ends when the goal is touched. The simplified proposed two-levels control system is shown in figure CONCLUSIONS An actual mobile robot conception is presented. The control system, based on two layers of competence, which operate in parallel, is the central part of this work. The first level performs the sensing and motor functions, so that the robot is able to move avoiding obstacles in an unknown environment. It can operate independently by possessing the skill to wander aimlessly.

6 Boris-Sergiu Cononovici, Gheorghe Niţu 330 A second layer of control enables the robot to navigate from the start point to a goal one by dead reckoning. When the second layer takes the robot control, it injects commands to the motor control, situated on the first layer, directing the robot toward the goal. The two control layers are implemented on two micro controllers running in parallel and changing messages between each other. The presented method adds additional levels of competence to the autonomous mobile robot. PILOT NAVIGATOR perception transition PO free way obstacle navigation PO obstacle avoidance motor monitor Figure 4 - Simplified two-levels control system. REFERENCES 1. BLOOM, H.R., CHO, H.S., A Sensor-Based Navigation for a Mobile Robot Using Fuzzy Logic and Reinforcement Learning, IEEE Transactions on Systems, Man and Cybernetics, Vol. 25, No. 3, pp , BROOKS, R.A., A Robust Layered Control System for a Mobile Robot, IEEE Journal of Robotics and Automation, Vol. 2, No. 1, pp , CONONOVICI, B.S., Reactive Behaviour of an Autonomous Mobile Robot Obtained by a Genetic Algorithm, Proceedings of the 2nd International Conference on Robotics, October 14-16, Timişoara / Reşiţa, Romania, pp , 2004; Robotică & Management, Vol. 9, No. 2, pp , CONONOVICI, B.S., A Sensor-Based Reactive Behaviour Obtained by Learning for a Mobile Robot, Proceedings of the Annual Symposium of the Institute of Solid Mechanics, May 19-20, Bucharest, Romania, CD-ROM, paper 3R, 8 pp, MILLAN, J. DEL R., Reinforcement Learning of Goal-Directed Obstacle-Avoiding Reaction Strategies in an Autonomous Mobile Robot, Robotics and Autonomous Systems, Vol. 15, pp , 1995.