Systems and methods for obstacle avoidance

• US 20070193798A1
• Filed: 10/20/2006
• Published: 08/23/2007
• Est. Priority Date: 10/21/2005
• Status: Active Grant

• Current Assignee: Deere & Company, iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Allard, James, Norris, William, Wienhold, Kathleen, Catalfano, Anthony
• Granted Patent: US 8,020,657 B2
• Time in Patent Office: Days
• US Class Current: 180/169
• CPC Class Codes: B60T 7/22 initiated by contact of vehicle, e.g. bumper, with an external object, e.g. another vehicle , or by means of contactless obstacle detectors mounted on the vehicle
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: B60W 60/0051 from occupants to vehicle
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: B62D 1/286 Systems for interrupting non-mechanical steering due to driver intervention
• CPC Class Codes: G05B 19/414 Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0251 extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision stereoscopic image analysis H04N13/00; depth recovery from images G06T7/593
• CPC Class Codes: G05D 1/0259 using magnetic or electromagnetic means
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G05D 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS
• CPC Class Codes: G05D 1/028 using a RF signal
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: Y10S 901/01 Mobile robot
• CPC Class Codes: Y10S 901/47 : Optical

Abstract

Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Claims

1. A robotically controlled vehicle comprising:

a robotic control unit comprising a control application;

a sensor for detecting object data representing detected obstacles or objects located outside of the robotic vehicle and transmitting the object data to the robotic control unit;

wherein the robotic control unit generates a map based on the object data, the map comprising map data, the map data including position data of detected obstacles or objects; and

wherein the control application unit decides vehicle actions, based at least in part on the map data, and outputs a control command representing the vehicle actions to a vehicle control unit.

2. The robotically controlled vehicle of claim 1, wherein the vehicle actions include at least one of vehicle velocity and vehicle direction.

3. The robotically controlled vehicle of claim 1, wherein the sensor is a laser scanner.

4. The robotically controlled vehicle of claim 1, wherein the robotic control unit comprises a processor and a memory having executable code, the executable code comprising a drive arbiter that receives two-dimensional map data and vehicle destination data and generates a set of vehicle actions based on, at least in part, the map data and vehicle destination data.

5. The robotically controlled vehicle of claim 4, wherein the set of vehicle actions comprise provider components that create vehicle actions and projector components that limit vehicle actions.

6. The robotically controlled vehicle of claim 5, wherein the provider components comprise at least one of a teleoperation component, “

Follow Me”

mode information, odometer waypoints, and GPS waypoints; and

wherein the projector components comprise map data.

7. The robotically controlled vehicle of claim 1, further comprising a vehicle control unit that receives vehicle actions from the robotic control unit and outputs control signals to a vehicle actuator.

8. The robotically controlled vehicle of claim 1, wherein the robotic control unit outputs control signals to a vehicle actuator.

9. The robotically controlled vehicle of claim 1, wherein the object data is three-dimensional data and the map data is two-dimensional data.

10. The robotically controlled vehicle of claim 1, wherein the sensor is a laser scanner assembly adapted to connect to a robotic vehicle, the laser scanner assembly comprising:

a laser scanner for transmitting a laser beam to detect the presence of an obstacle;

a scanner mechanism for manipulating the position of the laser scanner; and

a guard for protecting the laser scanner from damage and allow the laser beam to detect the presence of an obstacle, the guard comprising;

a base for connecting the laser scanner assembly to the robotic vehicle;

at least two support elements connected to the base; and

a plurality of support ribs connect to the at least two support elements.

11. The robotically controlled vehicle of claim 10, wherein the plurality of support ribs are positioned outside an angular window of the laser beam.

12. The robotically controlled vehicle of claim 10, wherein the plurality of support ribs have a first cross-sectional area and a second cross-sectional area larger than the first cross-sectional area;

and

wherein the plurality of support ribs are positioned such that the first cross-sectional area of the plurality of support ribs is in an angular window of the laser beam.

13. A method for directing a robotic vehicle to follow an object, the method comprising:

identifying an object for the robotic vehicle to follow;

estimating a robotic vehicle position relative to a previous position and a movement of the object;

estimating a range position of the object;

receiving a position of the object;

determining whether the object is located within the estimated range position;

calculating a trajectory set based in part on the object position, wherein the trajectory set comprises a plurality of trajectories;

assigning a preference value for each of the trajectories; and

providing the trajectory set to a drive arbiter.

14. The method of claim 13, wherein identifying an object for the robotic vehicle to follow comprises:

receiving an identification of an object to follow, the identification comprising an object location; and

detecting the object to follow.

15. The method of claim 13, wherein identifying an object for the robotic vehicle to follow comprises:

receiving data from a laser scanner, wherein the data comprises an identification of a plurality of objects within a detection zone; and

selecting the closest identified object to follow.

16. The method of claim 13, wherein the trajectory set comprises a trajectory having a middle vector and a plurality of trajectories having a trajectory vector, the middle vector and trajectory vector for each trajectory are separated from each other by a pre-determined angle.

17. The method of claim 16, wherein assigning a preference value for each of the trajectories comprises:

assigning a preferred value for the trajectory having the middle vector; and

assigning a least preferred value for the trajectory having the trajectory vector furthest from the middle vector.

18. The method of claim 13, further comprising:

receiving obstacle data, the obstacle data comprising the location of obstacles;

providing the obstacle data to the drive arbiter; and

selecting a trajectory based at least in part on the obstacle data.

19. A method for controlling a robotic vehicle using an obstacle map, the method comprising:

obtaining a plurality of points, wherein each point represents at least part of an obstacle and a position of the obstacle at a particular time;

associating a time stamp with each point;

mapping the points to a cell, wherein the cell is partitioned into grids;

separating the plurality of points into old, current, and new points based at least in part on the associated time stamp;

determining the center of at least one of the old points and the current points;

determining the center of the new points;

obtaining a position difference between the center of the new points and the center of at least one of the old points and the current points;

determining a velocity of an object based at least in part on the position difference; and

using the object velocity to control the robotic vehicle.

20. The method of claim 19, further comprising:

receiving a scan rate associated with obtaining the plurality of points;

determining a heading and radius of the object based at least in part on the position difference and scan rate; and

using the heading and radius to control the robotic vehicle.

21. The method of claim 19, further comprising:

generating a trajectory set comprising a plurality of trajectories, each trajectory comprising commands for robotic vehicle movement;

producing an obstacle report having obstacle characteristics, the obstacle report comprising a density of objects associated with a robotic vehicle path; and

using the obstacle report to assign a preference to each trajectory.

22. A method for generating a three-dimensional obstacle map for use in a robotically controlled vehicle, the method comprising;

using a laser scanner to execute a first scan of a scan range;

obtaining two-dimensional obstacle data points representing obstacles located in the scan range;

associating scan data with the obstacle data points, the scan data comprising at least one of scan range data representing the scan range, scanner angle data representing the angle of the laser scanner, vehicle velocity data, or a laser scanner synch pulse;

sending the scan data and obstacle data points to a robotic control unit;

time stamping the obstacle data points; and

generating a three-dimensional obstacle map based at least in part on the time stamped obstacle data points and scan data.

23. The method of claim 22, wherein sending the scan data and obstacle data points to a robotic control unit comprising sending the scan data and obstacle data points to a obstacle map robotic control unit;

and

wherein the obstacle map robotic control unit time stamps the obstacle data points.

24. The method of claim 23, further comprising:

providing a supervisory robotic control unit to generate the obstacle map.

25. The method of claim 22, wherein the obstacle map is used to control the robotic control vehicle.

26. A method for converting three-dimensional obstacle data into two-dimensional obstacle data for controlling a robotic vehicle, the method comprising:

obtaining a plurality of three-dimensional time stamped obstacle data from a laser scanner, the obstacle data representing the location of an obstacle;

receiving time stamped velocity data of the robotic vehicle;

comparing the obstacle data to pre-set criteria to separate the obstacle data into relevant obstacle data and irrelevant obstacle data, wherein the irrelevant obstacle data is outside the pre-set criteria;

discarding the irrelevant obstacle data;

correlating the relevant obstacle data to a two-dimensional point cloud representing an index of a point array; and

generating a two-dimensional obstacle map based at least in part on the point array.

27. The method of claim 26, further comprising:

discarding obstacle data having time stamps older than a pre-set threshold

28. The method of claim 26, further comprising:

filtering the point cloud to remove relevant obstacle data having a position beyond a pre-set length from the robotic control vehicle; and

overwriting obstacle map data having a time stamp outside a pre-set threshold with additional obstacle map data.

29. A robotic vehicle comprising:

a forward sensor assembly for executing a front range scan to obtain forward data representing obstacles or objects at least in front of the vehicle;

a rear sensor assembly for executing a rear range scan to obtain rear data representing obstacles or objects at least behind the vehicle; and

a robotic control unit for receiving the forward and rear data and generating an obstacle map based on the forward and rear data, the robotic control unit comprising;

the obstacle map;

a range guard application for detecting interruptions in the forward and rear data and substituting, based at least on the interruptions, data in the forward and rear data indicating the presence of obstacles in the forward and rear scan range; and

a control application for determining a trajectory based at least in part on the obstacle map and outputting control commands to a vehicle control unit based at least in part on the trajectory.

30. The robotic vehicle of claim 29, wherein the forward sensor assembly comprises a laser scanner.

31. The robotic vehicle of claim 29, wherein the rear sensor assembly comprises a laser scanner.

32. The robotic vehicle of claim 29, wherein the robotic vehicle is adapted to operate in a mode, the mode includes at least one of GPS waypoint, teleoperation, “

Follow Me,” and

teach and playback.

33. The robotic vehicle of claim 32, wherein the robotic control unit is adapted to alter a robotic control vehicle speed and direction as directed by the mode based on the obstacle map.