| Intelligent mobile robot is one of the hottest research field today. It can be the perfect replacement work properly for the laborious workers in the factory. It is not only able to reach moon, but also into that hot volcano to help people unlock the secrets of nature. In the complex environment under the water, it can replace the work dives into the water and even the deep water underwater operations. After earthquake disaster area, the flash floods and other disasters, often someone lost their lives due to lack of assistance, in this case, a robot can save these people. Now in the major cities, the robot restaurants have emerged, the robot waiters are on hand to tea and bottled water, a la carte orders. In the fields, the robot appears to improve the productivity and quality of crops, liberate of the labor force, allowing farmers to avoid harm from pesticides; they can also sing and dance, show acrobatics, as a performer they can be said to be both novel and stylish. Of course, it can also be a means of transport, such as car model car, passenger car balance. As UAV meets even the military field applications. Intelligent mobile robot is widely used, not list one by one here. The function of intelligent mobile robot is varied, also determines its different design requirements, and meet the design requirements for the corresponding mechanical structure, control system and program algorithm. A good robot, first of all, its mechanical agencies have to be very stable, must also is very reasonable, giving robots a stable work environment so as to reducing many uncertain factors bring tuning parameters for the inconvenience. And the second, must have their own senses, robot sensors, robot must know what to do next, or told the robot next decision with the help of a sensor sampling algorithm information provided to the program. Finally, and gives the robot "smart" step, a good algorithm is just like a clever mind, the correctness of the decision-making, the rate of reaction is important evaluation tagging of robot is good or bad.Based on service robot that a branch of intelligent mobile robot, carried out analysis and research, after many aspects of research found that along with the increasing of the national standard of living is improving continuously, the golf, table tennis, tennis and other activities have been combined with daily life, in second-tier cities can be seen everywhere all kinds of training and training venue. Every weekend is crowded, but at this stage the stadium has been gradually introduced to serve machine device such as a smart, although also be called a robot, but also is intelligent devices into the identity of the traditional sports. At first, this paper briefly expounds the research background and research significance of the topic, research status quo and direction of the technology of intelligent mobile robot at home and abroad. Secondly introduced in this paper, the robot’s design requirements. And then based on simple filter method, sampling value of sensor has carried on the simple processing, and use these finished samples values based on GPS positioning algorithm and based on the movement of the PID control algorithm. The simple path planning are introduced, and then presents a dynamic programming some of the basic case, the use of dynamic programming, this paper proposes a efficiency value to evaluate the standard of path planning algorithm, this algorithm can effectively improve the working efficiency of intelligent mobile robot closed ball.In this paper, the main work are the following:1. First problem to be solved is the positioning of the robot, with accurate positioning, to make intelligent mobile robot received the ball precisely navigate. This paper is selected as the NEO-6M GPS module robot positioning sensor. But in the course of the experiment, the noise GPS signals received ball bring intelligent mobile robot error seriously affected the localization algorithm intelligent mobile robots receive the ball. In order to solve the interference caused by noise, followed by an analysis of several common filtering method is simple and complex filter, through research and experiments, select the arithmetic mean value of the GPS filter for filtering the sample analysis, and integration of GPS gives feedback computing the distance between two points algorithm. Finally, to achieve the above-mentioned robot positioning.2. Although the smart move to close the ball robot already knows the distance between the two points, we can direct intelligent algorithm makes the robot move to close the ball constantly reduce the distance to reach the navigation function. But it will greatly reduce the efficiency of intelligent mobile robots receive the ball. To solve this problem, you must add the sensor, making intelligent mobile robot can receive the ball quickly and accurately learn the current direction of travel, so intelligent mobile robots work received the ball high efficiency. Select the electronic compass herein GY-26as an intelligent mobile robot navigation tool, in order to eliminate the navigation error, first by a first-order lag filter on the sampled values are processed electronic compass, followed by the introduction of a system of regulation and control algorithms to analyze the PID control and Fuzzy Control and practical advantages and disadvantages, the final selection of the PD controller as the regulation and control system of the robot and gives the tuning program.3. Positioning and navigation problem for intelligent mobile robot of this paper is to close the ball has been resolved. But without a good path planning, the robot can only work at a loss in the stadium, which makes the efficiency of intelligent mobile robot received the ball is greatly reduced. Study after study, analyzed the particularity of intelligent mobile robots work received the ball in the court, the results showed that in the course of research both in terms of the obstacles is usually fixed. After detailed analysis, in order to improve the efficiency of high-efficiency intelligent mobile robot received the ball, the author abandoned the traditional path planning algorithm, and then use dynamic programming of two classic cases,01knapsack problem and issue digital pyramids finished paper path design and planning algorithms. Finally, simulation experiments on simple analog map, through simulation, the validity of the approach. |
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