Method for dynamic correction during SLAM (simultaneous localization and map building) of mobile robot
A mobile robot and map creation technology, applied in the direction of navigation calculation tools, etc., can solve the problem of deviation between positioning and map influence, achieve the effect of improving accuracy and stability, and improving the path planning of mobile robots
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0058] Example 1
[0059] Such as Figure 1-3 As shown, this embodiment provides a dynamic correction method for simultaneous positioning and map creation of a mobile robot, which includes the following steps:
[0060] Step1: Data acquisition and verification,
[0061] Analyze and sort out the deviation factors caused by the historical information records in the real-time positioning and map construction;
[0062] Step2: Adjust the revision parameters,
[0063] First, initialize the mobile robot, the default starting position is zero,
[0064] Then, according to the posture information of the mobile robot at time t-1, that is, the posterior probability density function of t-1, the current state of the current time is predicted through the existing prior knowledge, and the prior density function at time t is obtained. The probability density function generates the collected particle set, collects N particles, and initializes the particle weights to 1 / N;
[0065] Then set the fitness funct...
Example Embodiment
[0111] Example 2
[0112] This embodiment provides a deduction process of a dynamic correction method for simultaneous positioning and map creation of a mobile robot. Each particle records the current position, speed and the optimal position that has been visited, representing a solution of the algorithm. During the iterative update process, each particle moves in the direction of the global optimal and the optimal position it has reached:
[0113]
[0114] X i (k)=X i (k)+V i (k+1)
[0115] X i (k) represents the position of the i-th particle in the k-th iteration, and the particle is based on V i (k+1) speed from position X i (k) Fly to X i (k+1) position, V i The speed of (k+1) is composed of three parts: inertia, cognition, and society. The inertial part simulates the bird's last trajectory. ω is the inertia weight, which represents the influence of the previous trajectory on the current new trajectory, c 1 And c 2 Is the acceleration coefficient of the cognitive part and the soc...
Example Embodiment
[0153] Example 3
[0154] This embodiment provides a dynamic correction method for simultaneous positioning and map creation of a mobile robot, which includes the following steps:
[0155] Establish the movement and observation model for Qt and Rt adjustment particles;
[0156] The proposed a priori knowledge correction FastSLAM algorithm adds Q before the particle update t And R t During the adjustment process, the method of updating and resampling each particle still uses the FastSLAM2.0 algorithm; due to Q t And R t The adjustment process is similar to the update process of FastSLAM2.0 particles. The adjustment process is used to adjust Q t And R t The pose and environment information of the mobile robot (based on different coordinate systems and origin positions) as a special particle X [ex] Look, Q t And R t The adjustment process is as follows:
[0157] 1) Initialization: If the number of road signs observed this time or last time is too small, the corresponding influence of cont...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap