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Self-adaptive dynamic window trajectory planning method for manned robot

A technology of dynamic window and trajectory planning, which is applied in the direction of motor vehicles, instruments, non-electric variable control, etc., and can solve problems such as the inability to meet the human-machine coexistence environment

Pending Publication Date: 2021-12-07
CIVIL AVIATION UNIV OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the existing research, most of the environments faced in the design of the trajectory planner are fixed obstacle scenes or set in special scenes, which cannot meet the needs of the human-machine coexistence environment.

Method used

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  • Self-adaptive dynamic window trajectory planning method for manned robot
  • Self-adaptive dynamic window trajectory planning method for manned robot
  • Self-adaptive dynamic window trajectory planning method for manned robot

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0140] Example 1: Simulation analysis of trajectory planning under different density levels of obstacles.

[0141] The obstacles in the human-machine coexistence environment are mainly pedestrians. When the crowd is relatively loose, the pedestrians can move freely without contact, and the pedestrian speed can be guaranteed at a normal level; There is a risk of mutual contact, and the flow rate of the crowd will be relatively reduced; when the crowd is loose, the manned robot can easily pass through the obstacle group during the operation; when the crowd density increases until the crowd is crowded, individual pedestrians When there is contact between robots, the robot cannot pass through the crowd, and needs to go around or even stop and wait.

[0142] (1) Planning simulation experiments in a crowded environment:

[0143] When designing the simulation experiment, by increasing the number of individual obstacles, a simulation scene corresponding to a relatively high density o...

Embodiment 2

[0151] Embodiment 2: Simulation analysis of traffic in the scene of sudden obstacles.

[0152] In order to study the planning effect when obstacles emerge, it is set as Figure 12 In the simulation scenario, when the robot runs at full speed to within 0.1m of the obstacle safety range at coordinates (6,6), a static obstacle appears at coordinates (6,6). At this time, according to Formula 13, the robot needs to increase the braking force sharply for emergency braking to ensure no collision. Such as Figure 13 As shown in the middle acceleration value and acceleration root mean square value, the robot can well guarantee the safety of trajectory planning when an obstacle suddenly appears, and the overall acceleration root mean square value at the braking moment reaches 18.53, which can achieve good control motion effect, but will be extremely uncomfortable.

[0153] exist Figure 14 The numerical results of the medium agility factor show that the traditional dynamic window al...

Embodiment 3

[0154] Embodiment 3: Simulation analysis of the scene of sharp turn with obstacles.

[0155] Aiming at the scene where the robot and the obstacle suddenly turn and move in the same direction in the complex human-machine coexistence environment, the following settings are set: Figure 16 In the simulation scene shown, the dotted line with arrows in the figure is the running route of dynamic obstacles, the dotted outline obstacle is the position on the way, the solid outline obstacle is the obstacle position at the end of the simulation, and the trajectory curve is the trajectory planning effect.

[0156] The simulation results show that the self-adaptive dynamic window algorithm can carry out safety planning in the scene of sharp turns with obstacles, and the vehicle acceleration can be modified online according to the actual situation combined with the formula. Temporary discomfort. according to Figure 18 The numerical value of the agility factor shows that the agility of t...

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Abstract

The invention belongs to the field of control engineering, and particularly relates to a self-adaptive dynamic window trajectory planning method for a manned robot. The method comprises the following steps: grading the density of a target group; designing an expansion equivalent model of the target; re-grading the density of the target group according to the expansion equivalent model of the target; designing a first braking acceleration of the robot; designing a second braking acceleration of the robot through a dynamic window method; optimizing the first braking acceleration and the second braking acceleration of the robot, and designing a self-adaptive dynamic window trajectory planning method. The method has the advantages that when trajectory planning is carried out on the mobile robot or the mobile carrier facing the loading application, the requirements for safety, agility and comfort of loading are met, and in the man-machine coexistence environment, many complex factors except for infrastructure obstacles contained in complex scenes are solved.

Description

technical field [0001] The invention belongs to the field of control engineering, and in particular relates to an adaptive dynamic window trajectory planning algorithm for a manned robot applied to a human-machine coexistence environment. Background technique [0002] In recent years, the application of manned robots in public environments such as terminals and railway stations has become a focus. The safety of manned robot operation and the comfort of passengers are the key issues to be solved, so it is necessary to study the smooth trajectory planning method of the robot from the perspective of the passenger. The main technical requirements for mobile robots or mobile vehicles for passenger applications are to meet the safety, agility, and comfort requirements of the vehicle when planning the trajectory. Not only the feasibility of robot trajectory planning needs to be considered, but also the comfort of the user or driver should be included in the design goals of the tra...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/024G05D1/0246G05D1/0257G05D1/0223G05D1/0225G05D1/0214G05D1/0221G05D1/0276
Inventor 高庆吉罗其俊侯世昊姜沅松
Owner CIVIL AVIATION UNIV OF CHINA
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