CN109557922B - Intelligent tractor field obstacle avoidance control system and method - Google Patents
Intelligent tractor field obstacle avoidance control system and method Download PDFInfo
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- 230000004927 fusion Effects 0.000 claims description 17
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
Abstract
The invention discloses a field obstacle avoidance control system and method for an intelligent tractor, and relates to the field of intelligent tractors, wherein the control system comprises an environment sensing module, a tractor information module, a decision module and a control execution module; the environment perception module and the tractor information module transmit acquired information to the decision module, the decision module processes the received information and transmits an action command to the lower controller after processing the information, the lower controller transmits the action command to the control execution module, and the control execution module controls the tractor to execute corresponding action; the control method is obtained based on the control system, different control algorithms and control operations can be realized aiming at different obstacles, the control precision requirement can be met in the algorithm control layer, the algorithm model can be simplified, and the method is suitable for the requirements of various obstacle avoidance complex working conditions.
Description
Technical Field
The invention belongs to the field of intelligent tractors, and particularly relates to a field obstacle avoidance control system and method for an intelligent tractor.
Background
In recent years, tractors in the field of domestic agricultural machinery have been developed rapidly, domestic tractors have already occupied the leading position of the domestic market, and with the penetration of the industries of intellectualization and electrification, tractor intellectualization is also a hot spot field of tractor research nowadays. During the actual field cultivation of the intelligent tractor, the situation that one or more obstacles exist in a cultivation path in the field is possibly encountered, and common obstacles comprise field markers, telegraph poles and the like. Therefore, the development of a control system capable of accurately identifying such obstacles and making accurate responses is crucial to the further development of intelligent tractors.
Disclosure of Invention
In order to solve the problems, the invention provides an intelligent tractor field obstacle avoidance control system, which solves the problem of intelligent tractor field obstacle avoidance to a certain extent, and can carry out different obstacle avoidance methods aiming at obstacles.
The invention is realized by the following technical scheme:
an intelligent tractor field obstacle avoidance control system comprises an environment sensing module, a tractor information module, a decision module and a control execution module; the environment perception module and the tractor information module transmit acquired information to the decision module, the decision module processes the received information and transmits action commands to the lower controller after processing the information, the lower controller sends the action commands to the control execution module, and the control execution module controls the tractor to execute corresponding actions.
Further, the environment sensing module comprises an ultrasonic sensor and a laser radar; the ultrasonic sensor is used for detecting the distance between the tractor and a front obstacle; the laser radar is used for detecting the shape and height related information of a front obstacle.
Further, the tractor information module comprises a GPS sensor and a vehicle speed sensor; the GPS sensor is used for detecting the position information of the vehicle in a map coordinate system, and the vehicle speed sensor is used for detecting the current running speed of the vehicle.
Furthermore, the control execution module comprises a liftable implement suspension, an electric accelerator, an electric brake, a steering motor and a gear switching mechanism; the liftable machine tool suspension is used for lifting the suspended machine tool to execute corresponding actions after the decision module instruction is obtained; the electric accelerator and the electric brake are used for executing corresponding operation and controlling the speed of the intelligent tractor after acquiring the instruction of the decision module; the steering motor is used for executing corresponding operation after acquiring the instruction of the decision module and controlling the intelligent tractor to steer; and the gear switching mechanism is used for executing corresponding operation after acquiring the instruction of the decision module and controlling the gear of the intelligent tractor to be switched to a forward gear or a backward gear.
Further, the decision module comprises an upper layer controller and a lower layer controller; the lower layer controller controls the operation execution module through the control quantity given by the upper layer controller; the upper layer controller is used for providing the control quantity required by the lower layer controller by adopting different algorithms through the information provided by the environment perception module and the tractor information module.
Further, the upper layer controller comprises an estimator fusion module, a hybrid controller and a planning module; the estimator fusion module is used for calculating the switching value of the hybrid controller according to the information detected from the outside; the hybrid controller is used for switching a corresponding control algorithm according to the switching quantity; the path planning module is used for planning the optimal paths in the given area, namely a left-turn traveling path and a right-turn traveling path according to the barrier signals.
The control method of the intelligent tractor field obstacle avoidance control system comprises the following steps:
the method comprises the following steps: an ultrasonic sensor in the environment sensing module continuously measures a front obstacle signal, and after the front obstacle distance signal obtained by the ultrasonic sensor reaches a certain distance, a laser radar sensor starts to measure the structural size of the front obstacle;
step two: an estimator fusion module in the upper layer controller acquires a front obstacle distance s through an ultrasonic sensor, acquires a front obstacle structure size through a laser radar, and acquires a tractor speed v through a tractor information module;
step three: the estimator fusion module processes the obstacle signals of the ultrasonic sensor and the laser radar sensor, judges the types of the obstacles, transmits the obstacle type signals to the hybrid controller and transmits the signals to the path planning module;
step four: the path planning module carries out optimal path planning according to the signals given by the estimator fusion module and transmits the path planning result to the hybrid controller;
step five: the hybrid controller receives the estimator fusion module signal, the path planning module signal and the vehicle speed sensor signal to make the following decisions:
firstly, the hybrid controller judges an obstacle signal: if judging that the obstacle can be surged, the hybrid controller transmits a lifting amount signal of the machine tool to a lower layer controller, and the lower layer controller controls the machine tool to be suspended to complete the lifting action: if the judgment result is that the obstacle cannot be surmounted, determining the turning direction of the tractor according to the path planning signal obtained by the path planning module and the path planning length, and selecting the path planning signal in the direction as an actual traveling path;
and then the hybrid controller calculates the tractor states at each time point in advance according to the planned path, and detects whether unsafe factors such as an overlarge steering wheel angle exist in the tractor states: if the safety requirements are met, calculating the control quantity of the actuating mechanism according to the algorithm 1 to obtain the height value of a lifting machine and the steering angle of the steering wheel at the moment, transmitting a signal to a lower layer controller, and controlling the lifting machine to lift and the steering wheel to steer by the lower layer controller: if the safety requirement is not met, calculating the stroke quantity of the electric brake and the height value of the lifting machine tool according to the algorithm 2 on the premise of considering the energy recovery of the motor, and transmitting the signal to a lower controller which controls the electric brake and the machine tool to be suspended to complete the specified action; and simultaneously, the upper layer controller sends out a capacitor charging circuit enabling signal. At this time, the power recovery device starts charging;
step six: after the hybrid controller stops the tractor according to the algorithm 2, the tractor returns to the rear of the original steering judgment point for a certain distance, and the backward operation performs the module execution operation according to the algorithm 3; and repeating the steps one) to five) until the intelligent tractor passes through the obstacle.
Further, the algorithm 1 is a PID algorithm, the algorithm 1 is used for completing driving according to a planned path, and the required operations are to lift the implement to a proper height and determine a steering angle of a steering wheel according to the path.
Further, the algorithm 2 adopts a fuzzy control method, and the algorithm 2 mainly considers the braking force required by the electric brake of the tractor behind the power recovery device and the driving safety of the tractor for braking.
Further, the algorithm 3 is an optimal control algorithm, the algorithm 3 mainly completes the back-up operation of the tractor, and the required operations are back-up and speed control; the gear switching mechanism is utilized to switch the gear of the intelligent tractor to a backward gear; the speed control of the tractor is completed by utilizing the electric accelerator and the electric brake.
The invention has the beneficial effects that:
1) the method can make a corresponding decision scheme aiming at field obstacles, and has positive significance for further development of the intelligent tractor.
2) The invention uses proper algorithms respectively according to different tractor operating conditions, thereby utilizing a simplified algorithm model to adapt to the use requirements of obstacles and field obstacle avoidance, the algorithm selects and integrates various factors such as the operation safety, the efficiency and the like of the tractor, and compared with the control by using a single algorithm, the invention can obtain excellent obstacle avoidance effect.
3) The power recovery system is added in the control system structure, so that the braking energy can be recovered to a greater extent under the condition of more field obstacles, and the endurance time of the tractor is prolonged.
Drawings
FIG. 1 is a schematic structural diagram of a control system and a control method for field obstacle avoidance of an intelligent tractor;
FIG. 2 is a schematic diagram of the decision block of FIG. 1;
FIG. 3 is a flow chart of the decision module algorithm of FIG. 1;
FIG. 4 is a block diagram of a power recovery system.
Detailed Description
For a further understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the accompanying drawing, in which:
referring to fig. 1, the intelligent tractor field obstacle avoidance control system based on the hybrid controller comprises an environment sensing module, a tractor information module, a decision module and a control execution module. The environment perception module comprises an ultrasonic sensor and a laser radar. The tractor information module comprises a GPS sensor and a vehicle speed sensor. The operation execution module comprises a liftable implement hanger, an electric throttle, an electric brake and a steering motor.
Referring to fig. 2, the decision module includes an upper layer controller and a lower layer controller. And the lower-layer controller controls the operation execution module through the control quantity given by the upper-layer controller. The upper layer controller is used for providing the control quantity required by the lower layer controller by adopting different algorithms through the information provided by the environment perception module and the tractor information module. The upper layer controller comprises an estimator fusion module and a hybrid controller. And the estimator fusion module is used for calculating the switching value of the hybrid controller according to the information detected from the outside. And the hybrid controller is used for switching the corresponding control algorithm according to the switching quantity. The estimation steps of the decision module in the upper layer controller are shown in conjunction with fig. 3.
The method comprises the following steps: the estimator fusion module acquires a front obstacle distance s through an ultrasonic sensor, acquires the length, width and height of a cubic range where the front obstacle is located through a laser radar, and acquires a tractor speed v through a tractor information module;
step two: the estimator fusion module determines the hybrid controller switching amount by the following method:
a) an obstacle estimator. Dividing the obstacle into a surmountable obstacle and an insurmountable obstacle according to the length, width and height of the obstacle;
b) if the brakes are immediately applied, the current tractor direction is assumed, and the minimum deceleration required is
The minimum deceleration is generated according to the braking energy recovery system and the electric brake, and the upper layer controller obtains the final braking stroke required to be executed by the electric brake through calculation
Step three: the estimator fusion module processes the obstacle signals of the ultrasonic sensor and the laser radar sensor, judges the types of the obstacles, transmits the obstacle type signals to the hybrid controller and transmits the signals to the path planning module;
step four: the path planning module estimates signals according to the ultrasonic sensor, the radar signals and the tractor running state and transmits path planning results to the hybrid controller;
step five: the hybrid controller receives the estimator fusion module signal, the path planning module signal and the vehicle speed sensor signal to make the following decisions:
firstly, the hybrid controller judges an obstacle signal: if judging that the obstacle can be surged, the hybrid controller transmits a lifting amount signal of the machine tool to a lower layer controller, and the lower layer controller controls the machine tool to be suspended to complete the lifting action: if the judgment result is that the obstacle cannot be exceeded, determining the turning direction of the tractor according to the path planning signal obtained by the path planning module and the path planning length, and selecting the path planning signal in the direction as an actual traveling path;
and secondly, the hybrid controller calculates the tractor states at each time point in advance according to the planned path, and detects whether unsafe factors such as an overlarge steering wheel angle exist in the tractor states. If the safety requirements are met, calculating the control quantity of the actuating mechanism according to the algorithm 1 to obtain the height value of a lifting machine and the steering angle of the steering wheel at the moment, transmitting a signal to a lower layer controller, and controlling the lifting machine to lift and the steering wheel to steer by the lower layer controller: if the safety requirement is not met, calculating the stroke quantity of the electric brake and the height value of the lifting machine tool according to the algorithm 2 on the premise of considering the energy recovery of the motor, and transmitting the signal to a lower controller which controls the electric brake and the machine tool to be suspended to complete the specified action; and simultaneously, the upper layer controller sends out a capacitor charging circuit enabling signal. At this time, the power recovery device starts charging;
step six: after the hybrid controller stops the tractor according to the algorithm 2, the tractor returns to the rear of the original execution steering judgment point by a certain distance, and the backward operation carries out execution module operation according to the algorithm 3; and repeating the steps one) to five) until the intelligent tractor passes through the obstacle.
Specific algorithms of algorithm 1, algorithm 2, and algorithm 3 are given below for reference.
Algorithm 1 essentially completes the travel according to the planned path, the required operations being raising the implement to the appropriate height and determining the steering angle of the steering wheel according to the path. Because all the quantities are given, a PID algorithm with relatively low precision but simple control can be adopted for control.
The algorithm 2 mainly performs braking through minimum deceleration and tractor safety, and as the control precision requirement is not high and a better control effect can be obtained through a more qualitative result, a fuzzy control method can be adopted for controlling, and braking is performed by considering the braking force required by the tractor electric brake after the power recovery device and the running safety of the tractor.
With reference to fig. 4, under algorithm 2, the power recovery system starts to operate: according to the ideal deceleration of the tractor, the controller controls the brake pedal to work, and simultaneously a super capacitor charging circuit connected with a tractor wheel shaft is connected, at the moment, the braking force of the tractor consists of two parts, and the braking force provided by the brake pedal and the dragging force generated by the generator shaft overcoming the magnetic field are used for braking. The power recovery system is connected with the storage battery power supply system in parallel: the power recovery system comprises a generator arranged on a tractor wheel shaft, a super capacitor charging circuit, a super capacitor and a super capacitor discharging circuit.
The power recovery system works as follows:
the method comprises the following steps: the upper layer controller controls an enabling switch in the super capacitor charging circuit to be closed, and the generator charges the super capacitor at the moment;
step two: when the braking process is finished and the charging process of the super capacitor is finished, the upper layer controller controls the enabling switch of the super capacitor charging circuit to be switched off;
step three: when the three conditions are met, the controller judges whether the internal capacity of the super capacitor meets the discharge requirement; if the discharge requirement is met, adjusting the output power of the super capacitor by using the super capacitor discharge circuit according to the electric energy requirements under different working conditions, so that the discharge working condition requirement is met; if the discharge requirement is not met, the discharge circuit of the super capacitor is disconnected, and the super capacitor does not work.
The electric energy of the super capacitor is used for the following three conditions
In the first case: because the output power of a common electric tractor is smaller than that of a traditional fuel vehicle in cultivation, under the cultivation environment, because the soil compaction degree is different, the output power of a motor required by operation is changed greatly when cultivation is carried out according to a common cultivation control strategy, and at the moment, the electric quantity stored by the super capacitor makes up the change amplitude of the output power of the motor;
in the second case: when the electric hanging tool needs to perform lifting action, electric energy is provided for lifting of the electric hanging tool;
in the third case: after the tractor finishes the farming working condition, under the ordinary transportation working condition, the super capacitor can assist the power supply, thereby prolonging the endurance time of the tractor.
Algorithm 3 essentially completes the tractor reverse operation, the required operations being reverse and speed control. The tractor is stopped at a more accurate parking position in backing, so that the following operation is facilitated, and the running efficiency is improved. Therefore, the optimal control algorithm is adopted to enable the control to be more accurate.
The present invention is not limited to the above-described embodiments, and any obvious improvements, substitutions or modifications can be made by those skilled in the art without departing from the spirit of the present invention.
Claims (4)
1. A control method of an intelligent tractor field obstacle avoidance control system is characterized by comprising an environment sensing module, a tractor information module, a decision module and a control execution module; the decision module comprises an upper layer controller and a lower layer controller; the lower layer controller controls the operation execution module through the control quantity given by the upper layer controller; the upper controller is used for providing the control quantity required by the lower controller by adopting different algorithms through the information provided by the environment sensing module and the tractor information module; the upper layer controller comprises an estimator fusion module, a hybrid controller and a path planning module; the estimator fusion module is used for calculating the switching value of the hybrid controller according to the information detected from the outside; the hybrid controller is used for switching a corresponding control algorithm according to the switching quantity; the path planning module is used for planning an optimal path in a given area, namely a left-turn traveling path and a right-turn traveling path according to the obstacle signal and the tractor running state estimation signal; the environment perception module and the tractor information module transmit the acquired information to the decision module, the decision module processes the received information and transmits an action command to the lower controller after processing the information, the lower controller transmits the action command to the operation execution module, and the operation execution module operates the tractor to execute corresponding action; the method comprises the following steps:
the method comprises the following steps: an ultrasonic sensor in the environment sensing module continuously measures a front obstacle signal, and after the front obstacle distance signal obtained by the ultrasonic sensor reaches a certain distance, a laser radar sensor starts to measure the structural size of the front obstacle;
step two: an estimator fusion module in the upper layer controller acquires a front obstacle distance s through an ultrasonic sensor, acquires a front obstacle structure size through a laser radar, and acquires a tractor speed v through a tractor information module;
step three: the estimator fusion module processes the obstacle signals of the ultrasonic sensor and the laser radar sensor, judges the types of the obstacles, transmits the obstacle type signals to the hybrid controller, and simultaneously transmits the obstacle type signals to the path planning module;
step four: the path planning module transmits a path planning result to the hybrid controller according to the ultrasonic sensor, the radar signal and the tractor running state estimation signal;
step five: the hybrid controller receives the estimator fusion module signal, the path planning module signal and the vehicle speed sensor signal to make the following decisions:
firstly, the hybrid controller judges an obstacle signal: if the obstacle surmountable is judged, the hybrid controller transmits a machine tool lifting amount signal to a lower layer controller, and the lower layer controller controls the machine tool to hang to complete the lifting action: if the judgment result is that the obstacle cannot be exceeded, determining the turning direction of the tractor according to the path planning signal obtained by the path planning module and the path planning length, and selecting the path planning signal in the direction as an actual traveling path;
and then the hybrid controller calculates tractor states at each time point in advance according to the planned path, and detects whether unsafe factors of an overlarge steering wheel angle exist in the tractor states: if the requirements on safety are met, calculating the control quantity of the actuating mechanism according to the algorithm 1 to obtain the height value of the lifting machine and the steering angle of the steering wheel at the moment of the height value of the lifting machine, transmitting signals of the height value of the lifting machine and the steering angle of the steering wheel to a lower layer controller, and controlling the lifting machine to lift by the lower layer controller and controlling the steering wheel to steer: if the safety requirement is not met, calculating the travel amount of the electric brake and the height value of the lifting machine tool according to the algorithm 2 on the premise of considering the energy recovery of the motor, transmitting the height value signal of the lifting machine tool to a lower layer controller, and controlling the electric brake and the machine tool to be suspended by the lower layer controller to finish the specified action; meanwhile, the upper controller sends out a capacitor charging circuit enabling signal; at this time, the power recovery device starts charging;
step six: after the hybrid controller stops the tractor according to the algorithm 2, the tractor returns to the rear of the original execution steering judgment point by a certain distance, and the backward operation carries out execution module operation according to the algorithm 3; repeating the steps from one to five until the intelligent tractor passes through the obstacle;
the algorithm 1 is a PID algorithm, the algorithm 1 is used for completing driving according to a planned path, and the required operation is to lift a machine to a proper height and determine a steering angle of a steering wheel according to the path;
the algorithm 2 adopts a fuzzy control method, and the algorithm 2 mainly takes the braking force required by the electric brake of the tractor behind the power recovery device and the driving safety of the tractor into consideration for braking;
the algorithm 3 is an optimal control algorithm, the algorithm 3 mainly completes the back-up operation of the tractor, and the required operations are back-up and speed control; the gear switching mechanism is utilized to switch the gear of the intelligent tractor to a backward gear; the speed control of the tractor is completed by utilizing the electric accelerator and the electric brake.
2. The control method of the intelligent tractor field obstacle avoidance control system of claim 1, wherein the environment sensing module comprises an ultrasonic sensor and a laser radar; the ultrasonic sensor is used for detecting the distance between the tractor and a front obstacle; the laser radar is used for detecting the shape and height related information of a front obstacle.
3. The control method of the intelligent tractor field obstacle avoidance control system according to claim 1, wherein the tractor information module comprises a GPS sensor and a vehicle speed sensor; the GPS sensor is used for detecting the position information of the vehicle in a map coordinate system, and the vehicle speed sensor is used for detecting the current running speed of the vehicle.
4. The control method of the intelligent tractor field obstacle avoidance control system according to claim 1, wherein the manipulation execution module comprises a liftable implement suspension, an electric throttle, an electric brake, a steering motor and a gear switching mechanism; the liftable machine tool suspension is used for lifting the suspended machine tool to execute corresponding actions after the decision module instruction is obtained; the electric accelerator and the electric brake are used for executing corresponding operation and controlling the speed of the intelligent tractor after acquiring the instruction of the decision module; the steering motor is used for executing corresponding operation after acquiring the instruction of the decision module and controlling the intelligent tractor to steer; and the gear switching mechanism is used for executing corresponding operation after acquiring the instruction of the decision module and controlling the intelligent tractor to switch the gear to the forward gear or the backward gear.
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| CN110100508A (en) * | 2019-04-23 | 2019-08-09 | 丰疆智能科技股份有限公司 | Equipment of ploughing and its plough tool protection system and guard method |
| CN110032193B (en) * | 2019-04-30 | 2020-07-03 | 盐城工业职业技术学院 | Intelligent tractor field obstacle avoidance control system and method |
| CN111026117B (en) * | 2019-12-17 | 2023-07-18 | 江苏大学 | Obstacle avoidance optimal control system and control method for intelligent rice transplanter |
| CN112298178A (en) * | 2020-11-09 | 2021-02-02 | 江苏悦达集团有限公司 | Unmanned tractor control system |
| CN112772146B (en) * | 2021-01-08 | 2022-01-11 | 江苏大学 | Transportation control system and linkage control method of orchard picking tractor |
| CN112896155B (en) * | 2021-02-24 | 2022-06-21 | 江苏大学 | Auxiliary control system and method for traction device of automatic driving tractor in orchard |
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