Kalman filter prediction-based robot obstacle avoidance method

A Kalman filter and robot technology, applied in the direction of using feedback control, etc., can solve the problems of use limitation, inability to avoid collision online, difficult to have prior knowledge, etc., and achieve the effect of simple implementation and good real-time performance.

Inactive Publication Date: 2011-01-12
SHAANXI UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

However, it is often difficult for robots to have prior knowledge of environmental information, especially information about dynamic obstacles. At the same time, mobile robots can only perform map creation in static environments, and cannot complete online collision avoidance in complex environments. The use of global path planning methods is limited

Method used

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  • Kalman filter prediction-based robot obstacle avoidance method
  • Kalman filter prediction-based robot obstacle avoidance method
  • Kalman filter prediction-based robot obstacle avoidance method

Examples

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Embodiment

[0058] figure 2 The robot initial path and the maneuvering target Kalman filter model state prediction trajectory shown in the figure, the robot and the maneuvering target move in a two-dimensional horizontal plane within the range of 90m × 70m. in:

[0059] Robot initial position: Start;

[0060] Dynamic target point: target.

[0061] Before the robot merges with the target, it must first arrive at the reconnaissance point B to complete a certain task;

[0062] The set of obstacles to avoid, the position of each obstacle ( Z x (i), Z y (i)), i= {1, 2, -- , N}, in the example, N is 12;

[0063] After the robot arrived at mission point B, its airborne sensors discovered a new low-to-medium speed maneuvering target;

[0064] The maneuverability of the robot is superior to other maneuvering targets;

[0065] The constraint condition of the robot's route planning is the shortest time to reach the goal under the premise of avoiding collisions;

[0066] The robot's maneuv...

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Abstract

The invention relates to a Kalman filter prediction-based robot obstacle avoidance method. In a complex environment, the robot travelling environment changes dynamically; and when an environment of a preplanned mission is determined to have a significant change, the target objective is modified, the target is planned in real time, and the path is modified. In the obstacle avoidance method, a path scheduler sorts a target set according to a digital map, the target set and the state of the robot acquired by a sensor system so as to generate a robot travelling point sequence; the robot travelling point sequence is executed by a servo system; when the sensor system detects a new obstacle, a Kalman filter model is established according to observation data; and parameters are identified and modified by using the observation data and an expectation maximization model identification algorithm of a classical linear dynamic system; and the digital map is updated for the next turn of local re-planning of the path scheduler. The method can realize obstacle avoidance path planning of the robot generated locally and dynamically in an undetermined environment, and has the advantages of simple implementation and good real-time performance.

Description

technical field [0001] The invention relates to a robot obstacle avoidance method based on Kalman filter prediction. Background technique [0002] With the continuous development of artificial intelligence and electronic communication technology, robots have not only entered military fields such as unmanned aerial vehicles and unmanned underwater robots, but also gradually entered into environmental monitoring such as weather forecasting, life-saving mission reconnaissance, search and forest wildfires. Civil life field. In a complex application environment, the robot's travel is dynamically changing and uncertain. Therefore, when it executes a planned task, once it is determined that the environment of the scheduled task has changed significantly, it should modify the task goal and re-plan the task in real time to Adapt to changes in the environment. Obstacle avoidance is one of the difficulties in robot path planning. Its task is to find a collision-free path from the ini...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D3/12
Inventor 郭文强侯勇严
Owner SHAANXI UNIV OF SCI & TECH
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