Humanoid Telexistence Control With Multi-User Mapping and Safety Checks
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Solution Overview
Problem
Existing telexistence systems are limited to single-user control of humanoid robots, lack real-time interaction capabilities for multiple users, and require expensive stationary maneuvering systems, hindering collaborative efforts and increasing operational costs.
Innovation Solution
A method and system enabling multi-user telexistence through a processor-controlled humanoid, allowing users to select mapping methods, verify joint weight loads, and grant control based on safety warnings, using limited hardware such as VR headsets and built-in cameras for body motion tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single user controls a humanoid remotely through VR headset and hand-held hardware, then the control precision and interaction quality are improved, but the system does not allow multiple users to remotely operate the humanoid successively
Solution Approach 1:
The system segments the control experience by providing two distinct mapping methods: humanoid-to-user mapping for precise control and user-to-humanoid mapping for collaborative operation. This segmentation allows different users to select appropriate mapping methods based on their needs, enabling both precise individual control and multi-user collaboration
Solution Approach 2:
The control system is designed with universal adaptability to support multiple users through configurable mapping methods. The system can function in different modes (humanoid-to-user or user-to-humanoid mapping) depending on user selection, making it versatile for both individual precise control and multi-user collaborative scenarios
2Ease of operation
If a stationary maneuvering system is used to control a humanoid, then the mapping of user actions to humanoid movements is improved, but the system cost increases significantly
Solution Approach 1:
The system replaces expensive stationary maneuvering systems with mobile computing devices (smartphones, tablets, laptops) equipped with cameras and sensors. The mechanical action mapping is achieved through software-based computer vision and sensor fusion algorithms rather than dedicated mechanical maneuvering hardware, significantly reducing system cost while maintaining mapping accuracy
Solution Approach 2:
The system creates a virtual copy of the user's actions through camera-based body motion tracking and sensor data. Instead of requiring physical maneuvering hardware, the system captures and processes visual and sensor data to generate control signals, providing accurate action mapping through software-based motion capture
3Speed
If humanoid-to-user mapping is used with significant joint weight load, then the control responsiveness is improved, but safety risks increase
Solution Approach 1:
The system implements continuous feedback by monitoring joint weight load through the humanoid's sensors and providing real-time warnings to users. When significant weight load is detected, the system alerts users to potential safety risks, allowing them to adjust their control strategy or take preventive actions, thus maintaining responsiveness while managing safety risks through informed user decision-making
Data Source
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AI summary
A method for performing telexistence, which may include receiving, by a processor, a request to control a humanoid from a remote user; determining, by the processor, acceptance of the request by a host; for the request being determined as accepted, verifying, by the processor, receipt of a set of initiating signals; for the set of initiating signals being received: receiving a humanoid mapping method chosen by the remote user, and controlling the humanoid based on the humanoid mapping method determined by the remote user; and for the set of initiating signals not being received, terminating, by the processor, the request to control the humanoid.