Position and direction determination using multiple single-channel encoders

• US 8,965,691 B1
• Filed: 10/05/2012
• Issued: 02/24/2015
• Est. Priority Date: 10/05/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Lombrozo, Pete
• Primary Examiner(s): Cheung, Calvin
• Assistant Examiner(s): Quillen, Allen E
• Application Number:
  US13/646,406
• Time in Patent Office: 872 Days
• Field of Search: 701/26, 701/69, 701/70, 701/116, 701/29.1, 701/30.5, 701/30.6, 701/41, 701/498, 701/23
• US Class Current: 701/498
• CPC Class Codes: B60W 2520/06 Direction of travel
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: G01D 5/2457 Incremental encoders having reference marks
• CPC Class Codes: G01P 13/04 Indicating positive or negative direction of a linear movement or clockwise or anti-clockwise direction of a rotational movement
• CPC Class Codes: G01P 13/045 with speed indication
• CPC Class Codes: G01P 3/481 of pulse signals

Abstract

A system for an autonomous vehicle is disclosed that combines information from single-channel encoders serving as wheel speed sensors on multiple wheels of the vehicle. A pattern of the outputs from the single-channel encoders is characterized while the vehicle is traveling in a first direction. A shift in the characterized pattern is associated with a change in direction of the autonomous vehicle. Such detection of changes in direction can be used to determine the position of the vehicle at low speeds or while starting and/or stopping where the vehicle can potentially rock back and forth.

Claims

1. A method comprising:

determining a low speed condition based on a decreasing velocity of a vehicle;

in response to the low speed condition, receiving, by a computing system, a first data stream from a first single channel encoder associated with a first wheel of the vehicle, the first data stream indicative of a first regularly repeating pattern with a frequency based on a rate of rotation of the first wheel;

receiving, by the computing system, a second data stream from a second single channel encoder associated with a second wheel of the vehicle, the second data stream indicative of a second regularly repeating pattern with a frequency based on a rate of rotation of the second wheel;

characterizing a time series relationship between the first and second regularly repeating patterns during a first time window corresponding to motion of the vehicle in a first direction;

during a second time window following the first time window, identifying a shift in the characterized time series relationship corresponding to a reversal in rotation direction of the first and second wheels;

responsive to identifying the shift, determining the vehicle is moving in a second direction substantially opposite the first direction; and

determining a time of direction reversal of the vehicle based on a timing of the identified shift.

2. The method according to claim 1, further comprising:

determining a speed of the vehicle prior to the determined time of direction reversal and a speed of the vehicle after the determined time of direction reversal, based in part on the frequencies of the first and second regularly repeating patterns indicative of the rates of rotation of the first and second wheels, respectively; and

determining a net displacement of the vehicle during a period that includes the determined time of reversal based on the determined speed of the vehicle while moving in the first direction, prior to the determined time of reversal, and based on the determined speed of the vehicle while moving in the second direction, following the determined time of reversal.

3. The method according to claim 2, further comprising:

estimating a position of the vehicle based on the determined net displacement;

identifying obstacles with the vehicle based on the estimated position;

determining a modified path of the vehicle that avoids the identified obstacles; and

controlling the vehicle to navigate along the modified path.

4. The method according to claim 1, wherein the characterizing the time series relationship includes determining a relative phase offset between the first and second regularly repeating patterns, and wherein the identified shift in the characterized time series relationship includes a change in sign of the relative phase offset.

5. The method according to claim 1, further comprising:

comparing the frequencies of the first and second regularly repeating patterns during the second window to identify a differential rate of rotation between the first and second wheels; and

predicting a bearing of the vehicle during the second time window based on the identified differential rate of rotation.

6. The method according to claim 1, wherein the first and second data streams are each indicative of a series of pulses with a fixed number of pulses for each complete rotation of the first and second wheel, respectively.

7. The method according to claim 1, further comprising:

receiving one or more additional data streams from one or more additional single channel encoders associated with one or more additional wheels of the vehicle, wherein the one or more additional data streams are indicative of one or more additional regularly repeating patterns with frequencies based on respective rates of rotation of the one or more additional wheels of the vehicle;

characterizing time series relationships among the one or more additional regularly repeating patterns and the first and second regularly repeating patterns; and

wherein determining the vehicle is moving in the second direction includes analyzing the additional regularly repeating patterns and the first and second regularly repeating patterns during the second time window to identify shifts in one or more of the characterized time series relationships corresponding to a reversal in rotation direction of the first wheel, the second wheel, and the one or more additional wheels.

8. The method according to claim 1, further comprising:

responsive to the frequency of the first and second regularly repeating patterns indicating a vehicle speed below a threshold value, repetitively analyzing the first and second data streams to characterize the time series relationship between the first and second regularly repeating patterns such that the time series relationship is recharacterized at least once per rotation of the first wheel.

9. The method according to claim 1, wherein the orientation of the first direction is determined based on one or more sensors configured to detect a motion of the vehicle with respect to its surroundings.

10. An autonomous vehicle system comprising:

a first single channel encoder associated with a first wheel of the autonomous vehicle and configured to generate a data stream indicative of a regularly repeating pattern with a frequency based on a rate of rotation of the first wheel;

a second single channel encoder associated with a second wheel of the autonomous vehicle and configured to generate a data stream indicative of a regularly repeating pattern with a frequency based on a rate of rotation of the second wheel; and

a controller configured to;

determine a low speed condition based on a decreasing velocity of the autonomous vehicle;

in response to the low speed condition, characterize a time series relationship between the first and second regularly repeating patterns during a first time window corresponding to motion of the vehicle in a first direction;

during a second time window following the first time window, identify a shift in the characterized time series relationship corresponding to a reversal in rotation direction of the first and second wheels;

responsive to identifying the shift in the characterized time series relationship, determine the vehicle is moving in a second direction substantially opposite the first direction; and

determine a time of direction reversal of the autonomous vehicle based on a timing of the identified shift.

11. The autonomous vehicle system according to claim 10, wherein the controller is further configured to:

determine a speed of the vehicle prior to the determined time of direction reversal and a speed of the vehicle after the determined time of direction reversal, based in part on the frequencies of the first and second regularly repeating patterns indicative of the rates of rotation of the first and second wheels, respectively; and

determine a net displacement of the vehicle during a period that includes the determined time of reversal based on the determined speed of the vehicle while moving in the first direction, prior to the determined time of reversal, and based on the determined speed of the vehicle while moving in the second direction, following the determined time of reversal.

12. The autonomous vehicle system according to claim 11, wherein the controller is further configured to:

estimate a position of the autonomous vehicle based on the determined net displacement;

identify obstacles with the vehicle based on the estimated position;

determine a modified path of the vehicle that avoids the identified obstacles; and

control the vehicle to navigate along the modified path.

13. The autonomous vehicle system according to claim 10, wherein the controller is further configured to:

determine a relative phase offset between the first and second regularly repeating patterns; and

identify the shift in the characterized time series relationship by identifying a change in sign of the relative phase offset.

14. The autonomous vehicle system according to claim 10, wherein the controller is further configured to:

compare the frequencies of the first and second regularly repeating patterns during the second window to identify a differential rate of rotation between the first and second wheels; and

predict a bearing of the vehicle during the second time window based on the identified differential rate of rotation.

15. The autonomous vehicle system according to claim 10, further comprising:

one or more additional single channel encoders associated with one or more additional wheels of the autonomous vehicle and configured to generate one or more additional data streams indicative of one or more additional regularly repeating patterns with frequencies based on respective rates of rotation of the one or more additional wheels of the autonomous vehicle; and

wherein the controller is further configured to;

characterize time series relationships among the one or more additional regularly repeating patterns and the first and second regularly repeating patterns; and

determine the vehicle is moving in the second direction by analyzing the additional regularly repeating patterns and the first and second regularly repeating patterns during the second time window to identify shifts in one or more of the characterized time series relationships corresponding to a reversal in rotation direction of the first wheel, the second wheel, and the one or more additional wheels.

16. The autonomous vehicle system according to claim 10, wherein the controller is further configured to:

responsive to the frequency of the first and second regularly repeating patterns indicating a vehicle speed below a threshold value, repetitively analyze the first and second data streams to characterize the time series relationship between the first and second regularly repeating patterns such that the time series relationship is recharacterized at least once per rotation of the first wheel.

17. A non-transitory computer readable medium storing instructions that, when executed by one or more processors in a computing device, cause the computing device to perform operations, the operations comprising:

determining a low speed condition based on a decreasing velocity of a vehicle;

in response to the low speed condition, receiving a first data stream from a first single channel encoder associated with a first wheel of the vehicle, the first data stream indicative of a first regularly repeating pattern with a frequency based on a rate of rotation of the first wheel;

receiving a second data stream from a second single channel encoder associated with a second wheel of the vehicle, the second data stream indicative of a second regularly repeating pattern with a frequency based on a rate of rotation of the second wheel;

characterizing a time series relationship between the first and second regularly repeating patterns during a first time window corresponding to motion of the vehicle in a first direction;

during a second time window following the first time window, identifying a shift in the characterized time series relationship corresponding to a reversal in rotation direction of the first and second wheels;

responsive to identifying the shift, determining the vehicle is moving in a second direction substantially opposite the first direction; and

determining a time of direction reversal of the vehicle based on a timing of the identified shift.

18. The non-transitory computer readable medium according to claim 17, wherein the operations further comprise:

determining a speed of the vehicle prior to the determined time of direction reversal and a speed of the vehicle after the determined time of direction reversal, based in part on the frequencies of the first and second regularly repeating patterns indicative of the rates of rotation of the first and second wheels, respectively; and

determining a net displacement of the vehicle during a period that includes the determined time of reversal based on the determined speed of the vehicle while moving in the first direction, prior to the determined time of reversal, and based on the determined speed of the vehicle while moving in the second direction, following the determined time of reversal.

19. The non-transitory computer readable medium according to claim 18, wherein the operations further comprise:

estimating a position of the vehicle based on the determined net displacement;

identifying obstacles with the vehicle based on the estimated position;

determining a modified path of the vehicle that avoids the identified obstacles; and

controlling the vehicle to navigate along the modified path.

20. The non-transitory computer readable medium according to claim 17, wherein the operations further comprise:

receiving one or more additional data streams from one or more additional single channel encoders associated with one or more additional wheels of the vehicle, wherein the one or more additional data streams are indicative of one or more additional regularly repeating patterns with frequencies based on respective rates of rotation of the one or more additional wheels of the vehicle;

analyzing the one or more additional data streams in combination with the first and second data streams to characterize time series relationships among the one or more additional regularly repeating patterns and the first and second regularly repeating patterns; and

wherein the determining the vehicle is moving in the second direction includes analyzing the additional regularly repeating patterns and the first and second regularly repeating patterns during the second time window to identify shifts in one or more of the characterized time series relationships corresponding to a reversal in rotation direction of the first wheel, the second wheel, and the one or more additional wheels.