IP Library › Granted Patent US 12,444,315
Granted Patent B2
US 12,444,315 · App. 18/492,156 · Granted Oct 14, 2025

Visualizing causality in mixed reality for manual task learning

Inventors: Karthik Ramani (West Lafayette, IN); Jingyu Shi (West Lafayette, IN); Rahul Jain (West Lafayette, IN)
Assignee: Purdue Research Foundation
G09B5/02G06F3/011G06T19/006G09B19/003G06T2200/24
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Quick Facts
Patent No.
US 12,444,315
App. No.
18/492,156
Granted
Oct 14, 2025
Kind
B2
Abstract

A learning system is disclosed that leverages intention-driven causality to enhance skill learning. The learning system enables an author to easily develop mixed reality (MR) tutorial content for performing a task that advantageously captures causal relationships between steps and, thus, enables such causality to be conveyed to the novice user when learning how to perform the task. To this end, the learning system leverages a novel hierarchical representation of causality and intention alongside a systematic workflow suitable for designing skill learning content. By preserving and presenting causal information to the novice user, the user can better understand not only the steps required to perform a task, but also why each step is performed.

Claims (54)

1. A method for generating instructional content, the method comprising:

storing, in a memory, virtual models representing virtual hands and at least one virtual object;

generating, with a processor, a sequence of pose data for the virtual hands and the at least one virtual object by recording, with at least one sensor, a demonstration by a user of a task within a real-world environment in which the user interacts with at least one real-world object corresponding to the at least one virtual object;

segmenting, with the processor, the sequence of pose data with at least three levels of granularity to define (i) a plurality of segments of the sequence of pose data, each respective segment of the plurality of segments corresponding to a respective step of a plurality of steps of the task, (ii) a plurality of groups of segments from the plurality of segments, each group of segments corresponding to a respective group of steps from the plurality of steps, and (iii) a respective plurality of subsegments for each respective step of the plurality of steps, each subsegment corresponding to a sub-step of the respective step;

defining, with the processor, (i) first causal relationships between steps of the plurality of steps of the task, (ii) second causal relationships between the groups of steps from the plurality of steps, and (iii) third causal relationships between the sub-steps of steps from the plurality of steps; and

generating, with the processor, graphical content configured to be displayed in an augmented reality graphical user interface to instruct a further user how to perform the task, based on the segmented sequence of pose data and the defined causal relationships, the graphical content being generated by rendering the plurality of virtual models posed according to the sequence of pose data for the virtual hands and the at least one virtual object, the graphical content including (i) a plurality of first graphical depictions of each step from the plurality of steps, (ii) a plurality of second graphical depictions of each group of steps from the plurality of steps, and (iii) a plurality of third graphical depictions of each sub-step of each step from the plurality of steps.

2. The method according to claim 1 , the defining the plurality of segments further comprising at least one of:

defining the plurality of segments based on user inputs; and

defining the plurality of groups of segments from the plurality of segments based on user inputs.

3. The method according to claim 1 , the defining the plurality of segments further comprising:

detecting, in the demonstration by the user of the task, interactions between hands of the user and the at least one real-world object; and

defining the plurality of groups of segments automatically based on the detected interactions between the hands of the user and the at least one real-world object, each group of segments corresponding to multiple interactions between the hands of the user and the at least one real-world object.

4. The method according to claim 1 , the defining the plurality of segments further comprising:

detecting, in the demonstration by the user of the task, interactions between hands of the user and the at least one real-world object; and

defining the plurality of segments automatically based on the detected interactions between the hands of the user and the at least one real-world object, each segment corresponding to a discrete interaction between the hands of the user and the at least one real-world object.

5. The method according to claim 1 , the defining causal relationships comprising:

generating a graph representation of the task including a plurality of first nodes and a plurality of first edges connecting nodes of the plurality of first nodes, each first node representing a respective step of the plurality of steps of the task, each respective first edge representing a causal relationship between steps represented by nodes connected by the respective first edge.

6. The method according to claim 5 , wherein the graph representation is a hierarchical graph representation that further includes:

a plurality of second nodes and a plurality of second edges connecting nodes of the plurality of second nodes, each second node representing a respective group of steps from the plurality of steps, each respective second edge representing a causal relationship between groups of steps represented by nodes connected by the respective second edge; and

a plurality of third nodes and a plurality of third edges connecting nodes of the plurality of third nodes, each third node representing a sub-step of a corresponding step from the plurality of steps, each respective second edge representing a causal relationship between sub-steps represented by nodes connected by the respective third edge.

7. The method according to claim 5 , wherein:

each step in the plurality of steps is a discrete interaction between the hands of the user and the at least one real-world object;

each group of steps from the plurality of steps represents a process necessary to complete the task that involves multiple discrete interactions between the hands of the user and the at least one real-world object; and

each sub-step of each respective step in the plurality of steps corresponds to a pose of at least one of (i) the virtual hands and (ii) the at least one virtual object that occurs during the discrete interaction corresponding to the respective step.

8. The method according to claim 1 , the defining the causal relationships further comprising:

defining a causal relationship between two respective steps of the plurality of steps of the task automatically depending on at least one of (i) which object of the at least one object is involved in the two respective steps during the demonstration and (ii) a temporal order of the two respective steps during the demonstration.

9. A method for providing instructional guidance for performing a task, the method comprising:

storing, in a memory, instructional data defining the task with at least two levels of granularity including (i) a plurality of steps of a task and causal relationships between steps of the plurality of steps of the task and (ii) groups of steps from the plurality of steps and causal relationships between the groups of steps from the plurality of steps, the plurality of steps including interactions with at least one real-world object in a real-world environment;

determining, with a processor, a current step that is being performed by a user by recording, with at least one sensor, a performance by the user of the task within the real-world environment; and

displaying, on a display, an augmented reality graphical user interface including graphical instructional elements that convey information regarding the plurality of steps of the task and that are superimposed on the real-world environment, the graphical instructional elements including:

(i) a first graphical depiction of the current step of the plurality of steps being performed by a user;

(ii) a second graphical depiction of at least one future step of the plurality of steps that has a causal relationship with the current step;

(iii) a third graphical depiction of a current group of steps of the plurality of steps being performed by the user; and

(iv) a fourth graphical depiction of at least one future group of steps of the plurality of steps that has a causal relationship with the current group of steps,

wherein the first graphical depiction, the second graphical depiction, the third graphical depiction, and the fourth graphical depiction are displayed simultaneously with one another in the augmented reality graphical user interface, and

wherein the augmented reality graphical user interface is automatically updated depending on the current step that is being performed by the user.

10. The method according to claim 9 , wherein the instructional data includes a graph representation of the task including a plurality of first nodes and a plurality of first edges connecting nodes of the plurality of first nodes, each first node representing a respective step of the plurality of steps of the task, each respective first edge representing a causal relationship between steps represented by nodes connected by the respective first edge.

11. The method according to claim 10 , wherein the graph representation is a hierarchical graph representation that further includes:

a plurality of second nodes and a plurality of second edges connecting nodes of the plurality of second nodes, each second node representing a respective group of steps from the plurality of steps, each respective second edge representing a causal relationship between groups of steps represented by nodes connected by the respective second edge; and

a plurality of third nodes and a plurality of third edges connecting nodes of the plurality of third nodes, each third node representing a sub-step of a corresponding step from the plurality of steps, each respective second edge representing a causal relationship between sub-steps represented by nodes connected by the respective third edge.

12. The method according to claim 9 , wherein:

the instructional data further defines sub-steps of steps in the plurality of steps and causal relationships between the sub-steps of steps from the plurality of steps; and

the graphical instructional elements in the augmented reality user interface further include (i) a fifth graphical depiction of a current sub-step of a current step of the plurality of steps being performed by the user and (ii) a sixth graphical depiction of at least one future sub-step of a step of the plurality of steps that has a causal relationship with the current sub-step, the fifth graphical depiction being displayed simultaneously with the sixth graphical depiction.

13. The method according to claim 12 , wherein:

each step in the plurality of steps is a discrete interaction between hands of the user and the at least one real-world object;

each group of steps from the plurality of steps represents a process necessary to complete the task that involves multiple discrete interactions between the hands of the user and the at least one real-world object; and

each sub-step of each respective step in the plurality of steps corresponds to a pose of at least one of (i) virtual hands and (ii) the at least one virtual object that occurs during the discrete interaction corresponding to the respective step.

14. The method according to claim 9 , wherein:

the instructional data includes a sequence of pose data for virtual hands and at least one virtual object corresponding to the at least one real-world object;

the first graphical depiction includes an animation of the current step, the animation being generated based on a segment of pose data from the sequence of pose data that corresponds to the current step; and

the second graphical depiction includes an animation of the at least one future step, the animation being generated based on a segment of pose data from the sequence of pose data that corresponds to the at least one future step.

15. The method according to claim 9 , wherein at least one of:

the first graphical depiction includes an image of the current step having a rendering of at least one of a virtual hand and a virtual object corresponding to the at least one real-world object; and

the second graphical depiction includes an image of the at least one future step having a rendering of at least one of the virtual hand and the virtual object corresponding to the at least one real-world object.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 8, 2023
From: RAMANI, KARTHIK; SHI, JINGYU; JAIN, RAHUL
To: PURDUE RESEARCH FOUNDATION
Reel/Frame 065810/0376 →
Continuity (4)
Provisional Application 63479810 · Jan 13, 2023
Provisional Application 63418609 · Oct 23, 2022
Related Publication 20240135831A1 · Apr 25, 2024
Related Publication 20240233563A9 · Jul 11, 2024
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