CN113031651B - Bilateral teleoperation control system and method of UAV hanging system based on value function approximation - Google Patents
Bilateral teleoperation control system and method of UAV hanging system based on value function approximation Download PDFInfo
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Abstract
The invention relates to a bilateral teleoperation control system and method of a UAV (unmanned aerial vehicle) hanging system based on value function approximation. The main end comprises a force feedback hand controller and a control computer, the slave end comprises a composite hanging system, the composite hanging system comprises a UAV and a suspension rope, the upper end of the suspension rope is fixed at the middle position of the lower side of the UAV, and a hanging load is fixed at the lower end of the suspension rope. The coupling relation between the UAV and the hanging load is established through the suspension ropes, the UAV hanging system adopts a value function approximation algorithm to carry out online learning, the complex modeling process of a composite hanging system is omitted, and the fast swing-free tracking of the hanging system to the given track of the main end is realized. The UAV hanging system establishes a bilateral teleoperation control model, introduces force/vision dual feedback, and clearly judges the carrying condition of the hanging load according to the feedback force of the slave end and the global view of the master end according to the physical interaction between the UAV and the obstacle and the hanging load, thereby enhancing the telepresence.
Description
Technical Field
The invention belongs to the technical field of bilateral teleoperation control of unmanned aerial vehicle hanging systems, and particularly relates to a bilateral teleoperation control system and method of a UAV hanging system based on value function approximation.
Background
In recent years, with the development of new materials, inertial navigation, micro electro mechanical systems and other technologies, low-cost and miniaturized Unmanned Aerial Vehicles (UAVs) represented by rotorcraft are increasingly emerging and are used, and UAV load transportation is prominent in civil and military fields. However, the conventional UAV system is a typical under-actuated system, and it is difficult to achieve UAV position control while suppressing oscillation of the yaw angle of the suspended load. The UAV suspension system control method has attracted extensive attention and research in the industry, and the research on suspension load mainly includes two directions: designing a controller to enable the swing of the suspended load to be kept stable quickly; the trajectory generation method allows the suspended load to reach a minimum swing with a fastest motion.
Further, considering the complexity of the UAV pylon system itself and the unpredictability of the operating environment, it is difficult to achieve the UAV pylon system with fully autonomous control for a long period of time in the future, and operator intervention is therefore essential. How to improve the telepresence of an operator, reduce the operation difficulty and realize the load suspension without swinging track running is an urgent problem to be solved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a bilateral teleoperation control system and method of a UAV (unmanned aerial vehicle) hanging system based on value function approximation. In a bilateral teleoperation control system of the UAV hanging system, a master end force feedback hand controller is used for controlling the hanging load pose of a slave end composite hanging system, and meanwhile, the composite hanging system adopts a value function approximation control algorithm to realize the generation and tracking of a hanging load without swing track in an obstacle environment, so that the maneuvering carrying task of the UAV hanging system is realized. Under the control mode, on one hand, the expected track of the hanging load is manually controlled, and the composite hanging system adopts a value function approximation control algorithm to realize the generation and tracking of the hanging load without swing track in the environment of the obstacle; on the other hand, the force feedback information of the composite hanging system is fed back to the main end through the force feedback hand controller, and meanwhile, the main end is combined with the control computer, so that the operator can feel as if he is at the scene, and the scene feeling and the quick response capability of the operator are improved.
The technical scheme adopted by the invention is as follows:
the UAV hanging system bilateral teleoperation control system based on value function approximation comprises a master end and a slave end, wherein the master end and the slave end are in communication connection through a wireless communication system; the master end comprises a force feedback hand controller and a control computer, and the force feedback hand controller is connected with the control computer; the slave end comprises a composite hanging system, the composite hanging system comprises a UAV and a suspension rope, the upper end of the suspension rope is fixed at the middle position of the lower side of the UAV, and a hanging load is fixed at the lower end of the suspension rope.
Further, the force feedback hand controller comprises a force feedback man-machine interaction device, and the force feedback man-machine interaction device is provided with 3 position degrees of freedom, 3 joint degrees of freedom and 3 position degrees of freedom force feedback outputs.
Further, the wireless communication system is a WIFI wireless network device.
A bilateral teleoperation control method of a UAV hanging system based on value function approximation comprises the following steps:
step one, establishing an organism coordinate system O-X L Y L Z L ，OX L Pointing to the front of the UAV body, OY L Pointing to the right side of the UAV body, OZ L Horizontally downwards, wherein the length of the suspension rope is L; establishing a bilateral teleoperation control model of the UAV hanging system;
secondly, controlling the trajectory of the UAV by using a force feedback hand controller, and performing online learning by using a composite hanging system according to a value function approximation algorithm to enable a hanging load to gradually present a swing-free trajectory in an obstacle environment and simultaneously generate force feedback information;
and thirdly, feeding back the force feedback information of the composite hanging system to the master end through a force feedback hand controller, and simultaneously combining a display picture of a control computer to obtain the force feedback information and a global view of the composite hanging system.
Further, in the first step, the bilateral teleoperation control model of the UAV hanging system comprises a force feedback human-computer interaction equipment dynamic model;
the dynamic model of the force feedback man-machine interaction equipment is shown as the following equation:
in the formula (1), q m ,
Sequentially representing the position, the speed and the acceleration vector of the end effector of the force feedback man-machine interaction equipment, M m (q m ) Is a matrix of the moments of inertia,
coriolis force and centrifugal force, g (q) m ) Is a gravity compensation term;
F m for controlling force applied on man-machine interface of man-machine interaction equipment fed back by main end force；F m ＝f h +f c Wherein, f h For control forces exerted on the force-feedback human-machine interaction device, f c Feedback force generated by interaction of the master end and the slave end;
master-slave end interactive feedback force f c Comprises the following steps:
f c ＝f e +f v (2)
in the formula (2), f e Repulsive force to the hanging load for obstacle environment, f v The position convergence force is adopted, so that the hanging load can track the given track of the main end without difference;
repulsive force f of obstacle environment to hanging load e The definition is as follows:
in the formula (3), k obs Is the barrier repulsive force coefficient, V i Is the virtual potential field of the i-th obstacle, q s Indicating the position, x, of the UAV oi Is the position of the ith obstacle, i e {1, …, n obs The number of obstacles, R is the radius of the maximum influence area of the obstacles, and R is the minimum safety distance between the UAV and the obstacles;
position convergence force f v The definition is as follows:
in the formula (4), e x ＝x d -x，e x For suspending load position errors, x d The desired position for the suspended load, x the actual position of the suspended load,
for hanging load speed errors, K 1 ∈R 3×3 And K 2 ∈R 3×3 Are all non-negative diagonal matrices.
Further, the second step comprises:
step 201, establishing 4-tuple in Markov decision process:
in equation (5), s is a set of state variables, and p ═ x y z] T In order to suspend the load position vector,
is a hanging load velocity vector;
is a hanging load acceleration vector; eta ═ alpha 1 α 2 ] T ，α 1 For suspending loads and plane X L OZ L Angle of included angle of alpha 2 For hanging load and plane Y L OZ L The included angle of (c);
for suspending loads and plane X L OZ L The angular velocity of the included angle of (a),
for suspending loads and plane Y L OZ L Angular velocity of the included angle of; a is an action; r(s) is a reward function, b 1 、b 2 And ε is a non-negative positive number, F(s) (| | v | | luminance 2 |η|| 2 ) Is a linear feature combination; p(s) 0 A) is the state transition probability;
step 202, determining a fitting model of the cost function:
in the formula (6), w is an introduction parameter;
determining an objective function to be optimized:
in the formula (7), E is the mean square value error, v(s) ═ r(s) + γ maxf(s) T w, r(s) is immediate award, maxF(s) T w is the maximum predicted reward in the future, and gamma is the discount coefficient;
the updating algorithm for determining parameters by using the gradient descent method is designed as follows:
in the formula (8), k is a non-negative positive number.
Furthermore, in the third step, the feedback force f generated by the interaction of the master and slave ends is the force feedback information of the composite suspension system c 。
The invention has the beneficial effects that:
in the invention, the coupling relation between the UAV and the hanging load is established through the suspension ropes, and the UAV hanging system adopts a value function approximation algorithm to carry out online learning, thereby omitting the complex modeling process of a composite hanging system and realizing the quick swing-free tracking of the hanging system to the given track of the main end. In addition, the UAV hanging system establishes a bilateral teleoperation control model, introduces force/vision dual feedback, and clearly judges the carrying condition of the hanging load according to the feedback force of the slave end and the global view of the master end according to the physical interaction between the UAV and the obstacle and the hanging load, so that the telepresence can be enhanced.
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FIG. 1 is a block diagram of a bilateral teleoperation control system for a UAV hitching system based on value function approximation of the present invention;
reference numerals are as follows: 1-master end, 11-force feedback hand controller, 12-control computer, 2-wireless communication system, 3-slave end, 31-composite suspension system, 311-UAV, 312-suspension load, 313-suspension rope.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
As shown in fig. 1, the UAV hitching system bilateral teleoperation control system based on value function approximation includes a master end 1 and a slave end 3, and the master end and the slave end are in communication connection through a wireless communication system 2. The master end 1 comprises a force feedback hand controller 11 and a control computer 12, and the force feedback hand controller 11 is connected with the control computer 12. The slave end 3 comprises a composite suspension system 31, the composite suspension system 31 comprises a UAV311 and a suspension rope 313, the upper end of the suspension rope 313 is fixed at the middle position of the lower side of the UAV311, and the lower end of the suspension rope 313 is fixed with a suspended load 312. In this embodiment, the force feedback hand controller 11 comprises a force feedback human-machine interaction device, and has 3 degrees of freedom of position, 3 degrees of freedom of joint, and 3 degrees of freedom of position force feedback output. The wireless communication system 2 is a WIFI wireless network device.
Referring to fig. 1, in the embodiment, a bilateral teleoperation control method of a UAV suspension system based on value function approximation is further provided, in which an operator 11 uses the UAV suspension bilateral teleoperation control system based on value function approximation to apply a force f h Acting on the force feedback hand controller 11, the force feedback hand controller 11 transmits the position information q m To the control computer 12; location information q m Sent to the slave 3 via the wireless communication system 2 to become the expected position signal x of the composite suspension system 31 d (ii) a The composite suspension system 31 realizes the generation and tracking of the suspension load 312 in the obstacle environment without swing track according to the value function approximation control algorithm. Meanwhile, the distance signal d between the composite suspension system 31 and the obstacle acts on the obstacle, and the obstacle provides the repulsive force f to the composite suspension system 31 e (environmental reaction force); the composite suspension system 31 is based on the repulsive force f e Output slave end force signal f c Outputs a main force signal F after passing through the wireless communication system 2 m Finally, the force feedback hand controller 11 acts on the operator to make the operator obtain the force feedback information of the slave composite hanging system 31. The operator obtains the global view of the slave-side composite hanging system 31 through the control computer 12 of the master side, and the telepresence of the operator is enhanced.
Specifically, the bilateral teleoperation control method of the UAV suspension system based on value function approximation comprises the following steps:
step one, establishing a body coordinate system O-X L Y L Z L ，OX L Pointing to the front of the UAV body, OY L Pointing to the right side of the UAV body, OZ L Horizontally downwards, the length of the suspension rope 313 is L; establishing a bilateral teleoperation control model of the UAV hanging system;
in the first step, the bilateral teleoperation control model of the UAV hanging system comprises a force feedback human-computer interaction equipment dynamic model;
the dynamic model of the force feedback human-computer interaction equipment is shown as the following equation:
in the formula (1), q m ,
Sequentially representing the position, the speed and the acceleration vector of the end effector of the force feedback man-machine interaction equipment, M m (q m ) Is a matrix of the moments of inertia,
coriolis force and centrifugal force, g (q) m ) Is a gravity compensation term;
F m feeding back control force on a man-machine interface of the man-machine interaction equipment for force applied to the main end 1; f m ＝f h +f c Wherein f is h For control forces exerted on the force-feedback human-machine interaction device, f c Feedback force generated by interaction of the master end and the slave end;
master-slave end interactive feedback force f c Comprises the following steps:
f c ＝f e +f v (2)
in the formula (2), f e Repulsive force, f, of the obstacle environment to the hanging load 312 v The position convergence force is applied, so that the hanging load 312 can track the given track of the main terminal 1 without difference;
barrier ringRepulsive force f of environment to hanging load 312 e The definition is as follows:
in the formula (3), k obs Is the barrier repulsive force coefficient, V i Is the virtual potential field of the i-th obstacle, q s Indicating the position, x, of the UAV311 oi Is the position of the ith obstacle, i e {1, …, n obs The number of obstacles, R is the radius of the maximum area of influence of the obstacles, R is the minimum safe distance between the UAV311 and the obstacles;
position convergence force f v The definition is as follows:
in the formula (4), e x ＝x d -x，e x To suspend a position error, x, of a load 312 d The desired position for suspended load 312, x the actual position of suspended load 312,
for hanging load 312 speed error, K 1 ∈R 3×3 And K 2 ∈R 3×3 Are all non-negative diagonal matrices.
Secondly, the operator controls the trajectory of the UAV311 by using the force feedback hand controller 11, and the composite hanging system 31 performs online learning according to a value function approximation algorithm, so that the hanging load 312 gradually presents a swing-free trajectory in an obstacle environment and simultaneously generates force feedback information; the method comprises the following steps:
step 201, establishing 4-tuple in Markov decision process:
in equation (5), s is a set of state variables, and p ═ x y z] T As a position vector of the hanging load 312，
Is the hanging load 312 velocity vector;
acceleration vector for hanging load 312; eta ═ alpha 1 α 2 ] T ，α 1 For hanging load 312 and plane X L OZ L Angle of included angle of alpha 2 For hanging load 312 and plane Y L OZ L The included angle of (c);
for hanging load 312 and plane X L OZ L The angular velocity of the included angle of (a),
for hanging load 312 and plane Y L OZ L Angular velocity of the included angle of; a is motion (i.e. acceleration in three directions x, y, z); r(s) is a reward function, b 1 、b 2 And ε is a non-negative positive number, F(s) (| | v | | luminance 2 ||η|| 2 ) Is a linear feature combination; p(s) 0 And a) is the state transition probability;
step 202, determining a fitting model of the cost function:
in the formula (6), w is an introduction parameter.
Determining an objective function to be optimized:
in the formula (7), E is the mean square value error, v(s) ═ r(s) + γ maxf(s) T w，r(s) immediate reward, maxF(s) T w is the future maximum predicted reward and γ is the discount coefficient.
The updating algorithm for determining parameters by using the gradient descent method is designed as follows:
in the formula (8), k is a non-negative positive number.
And step three, feeding back the force feedback information of the composite hanging system 31 to the main end 1 through the force feedback hand controller 11, and simultaneously combining the display picture of the control computer 12 to obtain the force feedback information and the global view of the composite hanging system 31. In step three, the feedback force f generated by the interaction of the master and slave ends is the force feedback information of the composite suspension system 31 c 。
On one hand, the advanced cognition of an operator is introduced into a control system, and the on-line decision of the operator is fully utilized to improve the operation capability of the robot; on the other hand, the slave-end UAV senses physical interaction with a hanging load and the surrounding environment, and feeds force/visual interaction information back to the master-end operator, so that the operator can feel like being personally on the scene, the telepresence and the quick response capability of the operator are obviously improved, and the working difficulty of the operator is reduced.
The above are only preferred embodiments of the present invention, and the scope of the present invention is not limited to the above examples, and all technical solutions that fall under the spirit of the present invention belong to the scope of the present invention. It should be noted that modifications and adaptations to those skilled in the art without departing from the principles of the present invention may be apparent to those skilled in the relevant art and are intended to be within the scope of the present invention.
Claims (6)
1. A bilateral teleoperation control method of a UAV hanging system based on value function approximation is characterized by comprising the following steps:
step one, establishing a body coordinate system O-X L Y L Z L ，OX L Pointing to the front of the UAV body, OY L Pointing to the right side of the UAV body, OZ L Horizontally down, suspension line (31)3) Is L; establishing a bilateral teleoperation control model of the UAV hanging system;
secondly, controlling the track of the UAV (311) by using the force feedback hand controller (11), and performing online learning by using the composite hanging system (31) according to a value function approximation algorithm to enable the hanging load (312) to gradually present a swing-free track in an obstacle environment and simultaneously generate force feedback information; the second step comprises the following steps:
step 201, establishing a 4-tuple of a Markov decision process:
in the formula (5), s is a state variable set, and p ═ x y z] T Is a position vector of the hanging load (312),
is a hanging load (312) velocity vector;
is a hanging load (312) acceleration vector; eta ═ alpha 1 α 2 ] T ，α 1 For suspending a load (312) and a plane X L OZ L Angle of included angle of alpha 2 For hanging load (312) and plane Y L OZ L The included angle of (c);
for suspending a load (312) and a plane X L OZ L The angular velocity of the included angle of (a),
for hanging load (312) and plane Y L OZ L Angular velocity of the included angle of; a is an action; r(s) is a reward function, b 1 、b 2 And ε is a non-negative positive number, F(s))＝(||v|| 2 ||η|| 2 ) Is a linear feature combination; p(s) 0 A) is the state transition probability;
step 202, determining a fitting model of the cost function:
in the formula (6), w is an introduction parameter;
determining an objective function to be optimized:
in equation (7), E is the mean square value error, v(s) ═ r(s) + γ max F(s) T w, r(s) is an immediate reward, max F(s) T w is the maximum predicted reward in the future, and gamma is the discount coefficient;
the updating algorithm for determining parameters by using the gradient descent method is designed as follows:
in the formula (8), k is a non-negative positive number;
and thirdly, feeding back the force feedback information of the composite hanging system (31) to the main end (1) through the force feedback hand controller (11), and simultaneously combining the display picture of the control computer (12) to obtain the force feedback information and the global view of the composite hanging system (31).
2. The UAV suspension system bilateral teleoperation control method of claim 1, wherein in step one, the UAV suspension system bilateral teleoperation control model comprises a force feedback human-machine interaction device dynamics model;
the dynamic model of the force feedback human-computer interaction equipment is shown as the following equation:
in the formula (1), q m ,
Sequentially representing the position, the speed and the acceleration vector of the end effector of the force feedback man-machine interaction equipment, M m (q m ) Is a matrix of the moments of inertia,
coriolis force and centrifugal force, g (q) m ) Is a gravity compensation term;
F m the control force applied on the man-machine interface of the man-machine interaction equipment is fed back by the force applied on the main end (1); f m ＝f h +f c Wherein f is h For control forces exerted on the force-feedback human-machine interaction device, f c Feedback force generated by interaction of the master end and the slave end;
master-slave end interactive feedback force f c Comprises the following steps:
f c ＝f e +f v (2)
in the formula (2), f e Repulsive force f of the obstacle environment to the suspended load (312) v The position convergence force is used, so that the hanging load (312) can track the given track of the main end (1) without difference;
repulsive force f of obstacle environment to hanging load (312) e The definition is as follows:
in the formula (3), k obs Is the barrier repulsive force coefficient, V i Is the virtual potential field of the i-th obstacle, q s Representing the position, x, of the UAV (311) oi Is the position of the ith obstacle, i e {1, …, n obs The number of obstacles, R is the radius of the maximum area of influence of the obstacles, and R is the UAV (311) and the obstaclesMinimum safe distance between obstacles;
position convergence force f v The definition is as follows:
in the formula (4), e x ＝x d -x，e x For hanging up a position error, x, of a load (312) d A desired position for the towed load (312), x an actual position for the towed load (312),
for hanging load (312) speed error, K 1 ∈R 3×3 And K 2 ∈R 3×3 Are all non-negative diagonal matrices.
3. The method for controlling bilateral teleoperation of UAV (unmanned aerial vehicle) suspension system based on value function approximation as claimed in claim 1, wherein in step three, the feedback force f generated by interaction of the master and slave ends is the force feedback information of the composite suspension system (31) c 。
4. The system of the UAV hanging system bilateral teleoperation control method based on the value function approximation is characterized by comprising a master end (1) and a slave end (3), wherein the master end and the slave end are in communication connection through a wireless communication system (2); the main end (1) comprises a force feedback hand controller (11) and a control computer (12), wherein the force feedback hand controller (11) is connected with the control computer (12); the slave end (3) comprises a composite hanging system (31), the composite hanging system (31) comprises a UAV (311) and a suspension rope (313), the upper end of the suspension rope (313) is fixed at the middle position of the lower side of the UAV (311), and a hanging load (312) is fixed at the lower end of the suspension rope (313).
5. The system of the UAV pendant system bilateral teleoperational control method of claim 4 where the force feedback hand controller (11) comprises a force feedback human-machine interface device with 3 degrees of freedom in position, 3 degrees of freedom in joint, and 3 degrees of freedom in position force feedback output.
6. The system of the UAV hanging system bilateral teleoperation control method based on value function approximation is characterized in that the wireless communication system (2) is a WIFI wireless network device.
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