A multi-cell filtering method for pose positioning of mobile robot in production workshop
A mobile robot and robot technology, which is applied in the field of multi-cell filtering, can solve the problem of low pose positioning accuracy, and achieve the effects of improving computational efficiency, avoiding the increase of dimension, and reducing the conservativeness of identification.
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Embodiment 1
[0043] This embodiment provides a mobile robot pose positioning method, the method comprising:
[0044] Step1: Discretize the kinematics model of the mobile robot into a discrete continuous model y k = φ k T θ * +e k , where φ k is the observation vector, θ is the pose positioning parameter, e k Indicates the bounded noise of the system;
[0045] Step2: Under the given unknown but bounded noise and external excitation signal, obtain the observation vector φ according to the kinematics model of the mobile robot k and the output sequence y k , and by observing the vector φ k and the output sequence y k Obtain the constraints of the kth step parameter feasible set;
[0046] Step3: According to the constraints of step k and the fully symmetrical polyhedron of step k-1, the fully symmetrical polyhedron with the smallest volume in step k is obtained;
[0047] Step4: Extend the fully symmetrical polyhedron obtained in Step3 to obtain the expanded fully symmetrical polyhedr...
Embodiment 2
[0050] In this embodiment, the application of the mobile robot pose positioning method provided in this application to a crawler mobile robot in a production workshop is introduced as an example:
[0051] Step 1: Go through the typical kinematics model of the crawler mobile robot in the production workshop, and then discretize it into a discrete continuous system y k = φ k T θ * +e k ;
[0052] A typical kinematic model of a crawler mobile robot in a production workshop:
[0053]
[0054] where (x k the y k ) T Indicates the current position of the robot, ψ k Indicates the robot angle, the current position of the robot and the robot angle can be measured by the sensor. ω 1,k , ω 2,k Respectively represent the rotational angular velocity of the left and right driving wheels, r represents the radius of the wheel, b represents the distance between the left and right wheels, ΔT represents the time interval, s 1,k , s 2,k Indicates the slip rate of the robot, (x k...
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