Multimodal Object Identification for Out-of-View Robot Commands
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Solution Overview
Problem
Robotics systems face challenges in disambiguating between multiple objects in their environment when a user provides a command referencing a specific object, especially when the object is out of view, leading to inaccurate object identification.
Innovation Solution
The system combines speech and image/video inputs to analyze user commands and gestures, using an inventory of the environment to narrow down the search for the intended object based on spatial region indicated by the gesture, improving object-locating accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robotics system searches the entire inventory for the referenced object, then it may find any instance of the object, but it cannot distinguish between multiple instances and may identify the wrong object
Solution Approach 1:
The system segments the search space by dividing the environment into multiple spatial regions (e.g., rooms, zones) and further into specific locations within those regions. This segmentation allows the system to narrow down the search from the entire inventory to specific regions indicated by user gestures, thereby improving object identification accuracy without requiring complex global search algorithms.
Solution Approach 2:
The system introduces an intermediary spatial mapping layer that connects user gestures to object locations. Instead of directly matching objects to commands, the system uses spatial region indicators (derived from gestures) as intermediaries to filter and identify the intended object from multiple instances in the inventory.
2Reliability
If the system uses only speech input to identify objects, then it can process commands simply, but it cannot disambiguate between multiple objects of the same type
Solution Approach 1:
The system merges multiple input modalities (speech recognition and gesture recognition) into a unified command interpretation process. Speech provides the object type while gestures provide spatial disambiguation, together enabling reliable identification of specific objects from multiple instances without significantly increasing system complexity.
Solution Approach 2:
The system adds a spatial dimension to the command interpretation process. Instead of relying solely on object type from speech (one-dimensional), the system incorporates spatial region information from gestures (adding another dimension), enabling disambiguation of multiple objects of the same type by their location.
3Productivity
If the system searches the entire environment for objects, then it ensures complete coverage, but it increases search time and computational resources
Solution Approach 1:
The system performs preliminary spatial mapping of the environment, organizing objects into regions and locations before the actual object search is needed. This preliminary organization allows rapid filtering of the inventory based on gesture-induced spatial constraints, significantly reducing search time while maintaining completeness within the relevant region.
Solution Approach 2:
The system applies local quality by focusing computational resources on specific spatial regions indicated by gestures rather than uniformly searching the entire environment. This localized search approach maintains productivity by reducing the search space while preserving search completeness within the relevant local region.
Data Source
AI summary
Methods, systems, and apparatus for receiving a command for controlling a robot, the command referencing an object, receiving sensor data for a portion of an environment of the robot, identifying, from the sensor data, a gesture of a human that indicates a spatial region located outside of the portion of the environment described by the sensor data, searching map data for the object, determining, based at least on searching the map data for the object referenced in the command, that the object referenced in the command is present in the spatial region, and in response to determining that the object referenced in the command is present in the spatial region, controlling the robot to perform an action with respect to the object referenced in the command.