Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A mobile robot local motion planning method and device

A mobile robot and local motion technology, applied in the field of robotics, can solve the scarcity hidden dangers of catastrophic events, nonlinear optimization problems and other problems

Active Publication Date: 2021-04-20
NINEBOT (BEIJING) TECH CO LTD
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, solving optimization problems is a challenge: since the objective function involves a dynamic model of the robot, and the constraints may consist of components related to complex geometry, optimization problems are usually nonlinear and difficult to solve in real-time on consumer robots with limited computing resources
However, the scarcity of catastrophic events in the training dataset remains a practical hazard

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A mobile robot local motion planning method and device
  • A mobile robot local motion planning method and device
  • A mobile robot local motion planning method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment approach

[0118] As an implementation manner, the determining the speed of the mobile robot includes:

[0119] determining the first position information of the mobile robot at the first moment;

[0120] Determining second position information of the mobile robot at a second moment; wherein, the first moment is a moment before the second moment;

[0121] Determine the speed of the mobile robot according to the first position information, the second position information, the first moment, and the second moment.

[0122] For example, the speed of the mobile robot=(second position information-first position information) / (second moment-first moment).

[0123] Certainly, the manner of determining the speed of the mobile robot is not limited to the form listed above, and may also be determined in other manners. For example, data is directly acquired from a speed sensor of the mobile robot to determine the speed of the mobile robot.

[0124] Step 103, based on the velocity and the 2d local ...

Embodiment 2

[0169] This embodiment provides a device for local motion planning of a mobile robot, the device comprising:

[0170] Preprocessor 10, used to determine the plane 2d local cost map image; determine the speed of the mobile robot;

[0171] The controller 20 is configured to formulate an action instruction for the mobile robot through a learning-based planner based on the velocity and the 2d local cost map image, so that the mobile robot executes the action instruction.

[0172] In the above solution, the mobile robot includes a learning-based planner.

[0173] As an implementation manner, the preprocessor 10 is specifically used for:

[0174] Obtaining data collected by predetermined sensors on the mobile robot;

[0175] Positioning the mobile robot based on the data, and simultaneously establishing a map of the surrounding environment where the mobile robot is located;

[0176] determining a local target point and a local obstacle map according to a given global path and the...

Embodiment 3

[0214] Based on the mobile robot local motion planning method and device described in Embodiment 1 and Embodiment 2, the method for local motion planning and obstacle avoidance of mobile robots proposed by us through deep imitation learning is given below. The main goal is to speed up local motion planning decisions for mobile robots, while making decision making as optimal, safe and general as possible.

[0215] A. System structure

[0216] image 3 Block diagram for a local mobility planning system with a policy network, from image 3 It can be seen that the system mainly includes two planning blocks. The first planning block is used to preprocess the raw sensing data and generate a local occupancy map describing surrounding obstacles and local target points extracted from the global path according to the robot pose. . These intermediate results are then fed into a second planning block where we employ a deep neural network to simulate a local planning strategy. Addition...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for local motion planning of a mobile robot, the method comprising: determining a plane (2d) local cost map image; determining the speed of the mobile robot; based on the speed and the 2d local cost map image, by A learning-based planner formulates motion instructions for the mobile robot to be executed by the mobile robot. The invention also discloses a mobile robot local motion planning device at the same time.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a method and device for local motion planning of a mobile robot. Background technique [0002] Motion planning for obstacle avoidance is one of the fundamental skills that intelligent mobile robots are expected to master. Various algorithms have been developed over the past decade to enable a robot to plan a trajectory to a goal point or follow a reference path without hitting obstacles. Despite significant progress, mobile robots are still far behind humans in mobility planning. For example, humans make motion decisions quickly with negligible effort, robustly adapt to uncertainties and unforeseen obstacles, and perform motion very smoothly and naturally. Given enough localized and global path information, such as Global Positioning System (GPS, Global Positioning System) and Google (Google) maps, people rely on powerful planning decision-making ability in different conditions ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02
CPCG05D1/0214G05D1/0223
Inventor 刘越江陈子冲
Owner NINEBOT (BEIJING) TECH CO LTD
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com