Robot Object Tracking for Detecting Target Exit From Camera Frame
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Solution Overview
Problem
Existing object tracking systems for robots face challenges in reliably determining the absence of a target object within a camera's field of view, particularly when using hand-mounted cameras, which are prone to errors due to external factors like light, and require technology to safely manipulate objects by explicitly recognizing their presence or absence.
Innovation Solution
An object tracking device and method utilizing a transformer-based model that includes a backbone, transformer encoder, decoder, bounding box prediction head, template update prediction head, and object exit prediction head to determine the location of a target object and predict its exit from the frame image, enabling safe manipulation by transmitting control signals to stop the robot when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a hand-mounted camera is used to track objects, then the robot can operate in various workspaces, but the reliability of object recognition deteriorates due to constant camera movement and external factors like light
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors object detection confidence levels and camera movement patterns. When reliability drops below a threshold due to movement or lighting changes, the system adjusts tracking parameters or requests re-acquisition, creating a closed-loop control that maintains recognition reliability despite hand-mounted camera constraints
Solution Approach 2:
The patent dynamically changes tracking parameters such as detection thresholds, integration times, and tracking algorithm sensitivity based on real-time conditions including camera acceleration data and lighting estimates. This adaptive parameter adjustment allows the system to maintain reliable object recognition across varying operational conditions while using a hand-mounted camera
2Extent of automation
If object tracking technology is used to recognize objects, then the robot can manipulate objects, but the ability to explicitly determine object absence deteriorates
Solution Approach 1:
The patent inverts the traditional tracking approach by explicitly modeling both object presence and object absence as detectable states. Instead of only tracking when objects are present, the system uses the tracking model's confidence outputs and temporal analysis to explicitly determine when objects have exited the field of view, converting the absence of detection into a positive detectable event
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes tracking confidence scores, temporal patterns, and camera motion data to determine object absence. This intermediary layer acts as a mediator between raw tracking data and control decisions, explicitly identifying when objects have left the field of view before triggering robot stop commands
3Productivity
If the robot continues operation without detecting object absence, then productivity is maintained, but safety deteriorates due to erroneous movements
Solution Approach 1:
The patent implements preliminary anti-action by proactively detecting object absence before the robot executes potentially harmful movements. The system continuously monitors for object exit conditions and preemptively issues stop commands when absence is detected, preventing erroneous movements rather than reacting to them after they occur
Solution Approach 2:
The patent uses feedback control where detection of object absence triggers immediate feedback to the robot control system to halt operations. This closed-loop safety mechanism ensures that productivity is maintained through continuous monitoring while preventing harmful movements by rapidly responding to object absence detections
Data Source
AI summary
The embodiments described herein are directed to an object tracking device and method for a robot that manipulates a moving object. An object tracking device according to one embodiment includes memory configured to store data and an object tracking model, and a controller including at least one processor and configured to determine whether a target object has exited from a frame image by using the object tracking model.