Humanoid Fall Direction Change Among Multiple Objects

• US 20100161126A1
• Filed: 12/17/2009
• Published: 06/24/2010
• Est. Priority Date: 12/19/2008
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: Sakagami, Yoshiaki, Nagarajan, Umashankar, Goswami, Ambarish
• Granted Patent: US 8,369,991 B2
• Time in Patent Office: Days
• US Class Current: 700/255
• CPC Class Codes: B62D 57/032 with alternately or sequentially lifted supporting base and legs; with alternately or sequentially lifted feet or skid B62D57/024 takes precedence

Abstract

A system and method is disclosed for controlling a robot having at least two legs, the robot falling down from an upright posture and the robot located near a plurality of surrounding objects. A plurality of predicted fall directions of the robot are determined, where each predicted fall direction is associated with a foot placement strategy, such as taking a step, for avoiding the surrounding objects. The degree to which each predicted fall direction avoids the surrounding objects is determined. A best strategy is selected from the various foot placement strategies based on the degree to which the associated fall direction avoids the surrounding objects. The robot is controlled to implement this best strategy.

Claims

1. A method for controlling a robot having at least two legs, the robot falling down from an upright posture and the robot located near a plurality of surrounding objects, the method comprising:

determining a plurality of predicted fall directions of the robot, each predicted fall direction associated with a foot placement strategy for avoiding the plurality of surrounding objects;

determining a degree to which each predicted fall direction avoids the plurality of surrounding objects;

selecting a best strategy from the plurality of foot placement strategies, the selecting based on the degree to which each predicted fall direction avoids the plurality of surrounding objects; and

controlling the robot to implement the best strategy.

2. The method of claim 1, wherein the best strategy comprises taking a step.

3. The method of claim 1, wherein the best strategy comprises lifting a leg.

4. The method of claim 1, further comprising, prior to determining a plurality of predicted fall directions:

determining whether the robot is steadily falling in a direction.

5. The method of claim 4, wherein determining whether the robot is steadily falling in a direction comprises:

computing a collinearity of a set of capture point trajectories of the robot over time.

6. The method of claim 1, wherein the plurality of predicted fall directions are determined using an inverted pendulum model of the robot.

7. The method of claim 1, wherein determining a plurality of predicted fall directions of the robot comprises:

determining a modified support polygon resulting from each foot placement strategy.

8. The method of claim 1, further comprising:

incorporating partial inertia shaping into the best strategy, wherein a center of pressure of the robot is used as a frame of reference for the partial inertia shaping.

9. The method of claim 1, wherein controlling the robot to implement the best strategy comprises:

controlling the robot to implement whole body inertia shaping.

10. A system for controlling a robot having at least two legs, the robot falling down from an upright posture and the robot located near a plurality of surrounding objects, the system comprising:

a computer-readable storage medium storing executable computer program modules configured for;

determining a plurality of predicted fall directions of the robot, each predicted fall direction associated with a foot placement strategy for avoiding the plurality of surrounding objects;

determining a degree to which each predicted fall direction avoids the plurality of surrounding objects;

selecting a best strategy from the plurality of foot placement strategies, the selecting based on the degree to which each predicted fall direction avoids the plurality of surrounding objects; and

controlling the robot to implement the best strategy.

11. The system of claim 10, wherein the best strategy comprises taking a step.

12. The system of claim 10, wherein the best strategy comprises lifting a leg.

13. The system of claim 10, wherein the modules are further configured for, prior to determining a plurality of predicted fall directions:

determining whether the robot is steadily falling in a direction.

14. The system of claim 13, wherein determining whether the robot is steadily falling in a direction comprises:

computing a collinearity of a set of capture point trajectories of the robot over time.

15. The system of claim 10, wherein the plurality of predicted fall directions are determined using an inverted pendulum model of the robot.

16. The system of claim 10, wherein determining a plurality of predicted fall directions of the robot comprises:

determining a modified support polygon resulting from each foot placement strategy.

17. The system of claim 10, wherein the modules are further configured for:

incorporating partial inertia shaping into the best strategy, wherein a center of pressure of the robot is used as a frame of reference for the partial inertia shaping.

18. The system of claim 10, wherein controlling the robot to implement the best strategy comprises:

controlling the robot to implement whole body inertia shaping.