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Patent Analysis of

Robotic Swarm Localization Using Ranging Radios

Updated Time 15 March 2019

Patent Registration Data

Publication Number

US20160114487A1

Application Number

US14/874078

Application Date

02 October 2015

Publication Date

28 April 2016

Current Assignee

LACAZE, ALBERTO DANIEL,MURPHY, KARL NICHOLAS,PUTNEY, JOSEPH,SCHNEIDER, ANNE RACHEL

Original Assignee (Applicant)

LACAZE, ALBERTO DANIEL,MURPHY, KARL NICHOLAS,PUTNEY, JOSEPH,SCHNEIDER, ANNE RACHEL

International Classification

B25J9/16,B25J5/00

Cooperative Classification

B25J9/1694,B25J9/1669,Y10S901/01,B25J5/00,B25J9/1666

Inventor

LACAZE, ALBERTO DANIEL,MURPHY, KARL NICHOLAS,PUTNEY, JOSEPH,SCHNEIDER, ANNE RACHEL

Patent Images

This patent contains figures and images illustrating the invention and its embodiment.

Robotic Swarm Localization Using Ranging Radios Robotic Swarm Localization Using Ranging Radios Robotic Swarm Localization Using Ranging Radios
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Abstract

A system for localizing a swarm of robotic platforms utilizing ranging sensors. The swarm is localized by purposely leaving some of the platforms of the swarm stationary, providing localization to the moving ones. The platforms in the swarm can alternate between a stationary and moving state.

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Claims

1. A method for robotic swarm localization using ranging sensors, comprising the steps of:providing a group of four or more moving platforms that are localized by: measuring the distance between the platforms using ranging sensors; and maintaining a stationary position by at least three platforms from the group at any given time.

2. The method for robotic swarm localization of claim 1, wherein the ranging sensors are ranging radios.

3. The method for robotic swarm localization of claim 2, wherein the ranging radios can be implemented with a variety of technologies, including electromagnetic waves with active or passive responses; LADAR; vision against known features in the moving platform; and acoustic sensors.

4. The method for robotic swarm localization of claim 1, wherein any ranging sensors that provide a point-to-point measurement between the platforms is utilized.

5. The method for robotic swarm localization of claim 1, further comprising the step of computing the localization using a combination of the ranging sensor data and other sensors and corresponding data in the moving platform.

6. The method for robotic swarm localization of claim 6, wherein the other sensors include one or more of the following sensors: inertial sensor; altimeter; compass; and pressure sensor.

7. The method for robotic swarm localization of claim 1, wherein the number of platforms maintaining a stationary position is more than three, to increase the localization space or accuracy of results.

8. The method for robotic swarm localization of claim 1, wherein the platforms maintaining a stationary position are located on the ground.

9. The method for robotic swarm localization of claim 1, further comprising the steps of traversing an area where stationary and moving platforms exchange functionality; one or more of the stationary platforms become moving platforms; and one or more of the moving platforms become stationary as long as at least three platforms are maintained stationary at any given time.

10. The method for robotic swarm localization of claim 1, further comprising the steps of creating an ad hoc localization structure; and moving the platforms into position by utilizing the stationary platforms.

11. The method for robotic swarm localization of claim 10, further comprising the step of coordinating the movement of the platforms to zero out the acceleration biases each time that they land.

12. The method for robotic swarm localization of claim 11, further comprising the step of controlling the size of the hops between zero velocity updates to match the drift of the accelerometers.

13. The method for robotic swarm localization of claim 1, further comprising the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.

14. The method for robotic swarm localization of claim 1, wherein the swarm is composed of either or ground, underwater, surface, or flying platforms.

15. The method for robotic swarm localization of claim 14, wherein the platforms can be manned or unmanned.

16. A method for robotic swarm localization using ranging sensors, comprising the steps of:a group of one or more moving platforms that are localized by: ranging sensors capable of measuring the distance between the platforms; and the platforms leave behind/drop/marsupial setup at least three sensors that are maintained stationary at the same time.

17. The method for robotic swarm localization of claim 16, further comprising the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.

18. The method for robotic swarm localization of claim 16, wherein the swarm is composed of either or ground, underwater, surface, or flying platforms.

19. The method for robotic swarm localization of claim 18, wherein the platforms can be manned or unmanned.

20. A method for robotic swarm localization using ranging sensors, comprising the steps of:a group of moving platforms that are localized by: ranging sensors capable of measuring the distance between the platforms; and at least three sensors left behind by another mechanism other than the platform in ad hoc positions that are maintained stationary at the same time.

21. The method for robotic swarm localization of claim 20, further comprising the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.

22. The method for robotic swarm localization of claim 20, wherein the swarm is composed of either or ground, underwater, surface, or flying platforms.

23. The method for robotic swarm localization of claim 22, wherein the platforms can be manned or unmanned.

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Claim Tree

  • 1
    1. A method for robotic swarm localization using ranging sensors, comprising
    • the steps of:providing a group of four or more moving platforms that are localized by: measuring the distance between the platforms using ranging sensors
    • and maintaining a stationary position by at least three platforms from the group at any given time.
    • 2. The method for robotic swarm localization of claim 1, wherein
      • the ranging sensors are ranging radios.
    • 4. The method for robotic swarm localization of claim 1, wherein
      • any ranging sensors that provide a point-to-point measurement between the platforms is utilized.
    • 5. The method for robotic swarm localization of claim 1, further comprising
      • the step of computing the localization using a combination of the ranging sensor data and other sensors and corresponding data in the moving platform.
    • 7. The method for robotic swarm localization of claim 1, wherein
      • the number of platforms maintaining a stationary position is more than three, to increase the localization space or accuracy of results.
    • 8. The method for robotic swarm localization of claim 1, wherein
      • the platforms maintaining a stationary position are located on the ground.
    • 9. The method for robotic swarm localization of claim 1, further comprising
      • the steps of traversing an area where stationary and moving platforms exchange functionality
      • one or more of the stationary platforms become moving platforms
      • and one or more of the moving platforms become stationary as long as at least three platforms are maintained stationary at any given time.
    • 10. The method for robotic swarm localization of claim 1, further comprising
      • the steps of creating an ad hoc localization structure
      • and moving the platforms into position by utilizing the stationary platforms.
    • 13. The method for robotic swarm localization of claim 1, further comprising
      • the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.
    • 14. The method for robotic swarm localization of claim 1, wherein
      • the swarm is composed of
  • 16
    16. A method for robotic swarm localization using ranging sensors, comprising
    • the steps of:a group of one or more moving platforms that are localized by: ranging sensors capable of measuring the distance between the platforms
    • and the platforms leave behind/drop/marsupial setup at least three sensors that are maintained stationary at the same time.
    • 17. The method for robotic swarm localization of claim 16, further comprising
      • the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.
    • 18. The method for robotic swarm localization of claim 16, wherein
      • the swarm is composed of
  • 20
    20. A method for robotic swarm localization using ranging sensors, comprising
    • the steps of:a group of moving platforms that are localized by: ranging sensors capable of measuring the distance between the platforms
    • and at least three sensors left behind by another mechanism other than the platform in ad hoc positions that are maintained stationary at the same time.
    • 21. The method for robotic swarm localization of claim 20, further comprising
      • the step of optimizing the topology of the platforms or sensors left stationary as to minimize the error propagation of this swarm.
    • 22. The method for robotic swarm localization of claim 20, wherein
      • the swarm is composed of
See all 3 independent claims

Description

FEDERALLY SPONSORED RESEARCH

Not Applicable

SEQUENCE LISTING OR PROGRAM

Not Applicable

TECHNICAL FIELD OF THE INVENTION

The present invention relates generally to the autonomous control of small robotic platforms. More specifically, the present invention relates to robotic localization.

BACKGROUND OF THE INVENTION

There are several challenges related to the autonomous control of small robotic platforms. The small payload and usually low cost restrict them from carrying accurate, inertial localization systems. Therefore, in GPS denied areas, automatic tasks—like mapping and searching—become a challenge.

Several technologies have been developed to overcome these challenges. Visual odometry and LADAR odometry are commonly used to complement the higher drift of the inertial components, aiding in localization. The problem with these techniques is that they are brittle in some environments; in particular, tunnels, caves, and man-made structures pose some challenges. Poor lighting conditions, low quality cameras, and dusty or smoky conditions further exacerbate the localization errors. For example, state-of-the-art quadrotors equipped with quality cameras, flying in a sufficiently-lit tunnel, while using visual odometry, may achieve 5% to 10% error as a function of distance travelled. This error becomes 10% to 25% of distance travelled if the quad-rotor must carry its own illumination. If the tunnel is dusty or smoky, the error in localization is driven by the inertial components.

The inertial components of the navigation unit are composed of accelerometers and gyroscopes. The position is computed by double integrating the acceleration. Therefore, small bias errors in acceleration become exponential errors in position. If the visual or LADAR odometry is blocked by smoke or dust, and no longer seeing features, the position error will grow exponentially. This is due to the double integration errors, and the lack of other sensors contributing to the bias estimates.

The problems with localization become very evident on flying platforms, as they do not have wheel odometry to maintain the inertial biases. In small robotic platforms where the wheel slippage is large, the localization estimates also suffer accordingly.

SUMMARY OF THE INVENTION

The invention provides a mechanism for maintaining the localization of moving platforms, by utilizing stationary platforms, moving platforms, and ranging radios. The stationary platforms help provide localization to the moving platforms. The number of stationary platforms can be increased to provide higher accuracy, or to extend the localization workspace. By alternating stationary and moving platforms, the localization workspace can be accommodated to the task.

Ranging radios often provide a single measurement of range, without providing the direction of the other device. However, there are ranging radios that can provide both range and direction. If this type of ranging radios are used, then a single platform can be left stationary, while the others can move. The ranging radios can be implemented with a variety of technologies, including electromagnetic waves with active or passive responses (i.e. radar), utilizing LADAR, vision against known features in the moving platform, and even acoustic sensors. This localization system can be utilized with a variety of sensors that provide point-to-point measurement between the platforms.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate the present invention and, together with the description, further serve to explain the principles of the invention and to enable a person skilled in the pertinent art to make and use the invention.

FIGS. 1a, 1b, and 1c illustrate the localization swarm on the fly; and

FIG. 2 illustrates a group of quads is maintained stationary on the ground to provide a localization pathway for the fling quads.

DETAILED DESCRIPTION OF THE INVENTION

In the following detailed description of the invention of exemplary embodiments of the invention, reference is made to the accompanying drawings (where like numbers represent like elements), which form a part hereof, and in which is shown by way of illustration specific exemplary embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, but other embodiments may be utilized and logical, mechanical, electrical, and other changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims.

In the following description, numerous specific details are set forth to provide a thorough understanding of the invention. However, it is understood that the invention may be practiced without these specific details. In other instances, well-known structures and techniques known to one of ordinary skill in the art have not been shown in detail in order not to obscure the invention. Referring to the figures, it is possible to see the various major elements constituting the apparatus of the present invention.

Ranging radios operating at ultra wide band (UWB) frequencies can provide accurate point-to-point measurements. The accuracy of the range measurements depends on the frequencies used and the radio's design. Commercial, off-the-shelf ranging radios are available utilizing UWB, but there are also ranging radios based on BLUETOOTH, WIFI, and other frequencies and encoding methods. State-of-the-art ranging radios are small in size and low in cost. This makes them prime candidates for installation in small robotic systems.

By installing ranging radios, we can directly measure the distance between the robotic platforms, but they do not provide localization by default. The invention provides a swarm movement methodology for maintaining relative and absolute localization of the group.

As presented earlier, the inertial components of navigation units drift with time as a platform is flying. However, when the navigation unit is not moving (i.e. the platform has landed), we are aware that the position is immobile; acceleration biases can then be computed (zero velocity update). Moreover, if a sufficient number of platforms are not moving, the position of the moving platforms can be computed by triangulating the position of the ones that are stationary.

Specifically, let's assume that the position of three quadrotors is known. The quads are on the ground 101, 102, and 103 in a triangular configuration shown in FIG. 1a, 104. There are three other quads 105, 106, and 107 that “leap frog” over the three landed quads 101, 102, and 103. Since the location of all the robots/quads on the ground 101, 102, and 103 is known, and the ranging radios provide ranges from each landed quad 101, 102, and 103 to each flying quad 105, 106, and 107, the location of the three flying quads 105, 106, and 107 is also known. As the flying quads land as shown in FIG. 1b, 108, the location of their landing will be known, releasing the originally landed quads 101, 102, and 103 to fly, starting the cycle once again as shown in FIG. 1c, 109.

Even though the example of FIGS. 1a-1c shows the quads “leap frogging,” the same algorithm can be used with at least three stationary robots, where the flying robots perform other tasks (like mapping the room), leaving the three stationary robots in place, acting as sources of localization.

In a similar fashion, more than three robots can be used in a stationary manner to create a localization “carpet”207 that can provide both localization and communication relay. FIG. 2 shows one such example. In this case, a group of stationary quads 201, 202, 203, 204, and 205 which may be low on battery, are being used to provide localization for the incoming wave of flying quads 206 that are traversing a path 208.

Different vehicle topologies (stationary vehicles) will provide different error propagation for the swarm. In order to optimize the topology and therefore minimize the error in localization, the system can search for the most effective topology. The literature already presents a variety of optimization algorithms that can be used for this purpose. In particular, a lot of work in this area was conducted in the early 70s and 80s to find the best topology for GPS satellites. In the present incarnation the topology is generated by expanding a multi-vehicle search. Other search algorithms like visibility graph-based, DIJKSTRA, neural networks, or even simplex methods can be used.

Thus, it is appreciated that the optimum dimensional relationships for the parts of the invention, to include variation in size, materials, shape, form, function, and manner of operation, assembly and use, are deemed readily apparent and obvious to one of ordinary skill in the art, and all equivalent relationships to those illustrated in the drawings and described in the above description are intended to be encompassed by the present invention.

Furthermore, other areas of art may benefit from this method and adjustments to the design are anticipated. Thus, the scope of the invention should be determined by the appended claims and their legal equivalents, rather than by the examples given.

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Patent Valuation

41.0/100 Score

Market Attractiveness

It shows from an IP point of view how many competitors are active and innovations are made in the different technical fields of the company. On a company level, the market attractiveness is often also an indicator of how diversified a company is. Here we look into the commercial relevance of the market.

9.0/100 Score

Market Coverage

It shows the sizes of the market that is covered with the IP and in how many countries the IP guarantees protection. It reflects a market size that is potentially addressable with the invented technology/formulation with a legal protection which also includes a freedom to operate. Here we look into the size of the impacted market.

40.0/100 Score

Technology Quality

It shows the degree of innovation that can be derived from a company’s IP. Here we look into ease of detection, ability to design around and significance of the patented feature to the product/service.

22.0/100 Score

Assignee Score

It takes the R&D behavior of the company itself into account that results in IP. During the invention phase, larger companies are considered to assign a higher R&D budget on a certain technology field, these companies have a better influence on their market, on what is marketable and what might lead to a standard.

15.0/100 Score

Legal Score

It shows the legal strength of IP in terms of its degree of protecting effect. Here we look into claim scope, claim breadth, claim quality, stability and priority.

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