Torso Motion Estimation for Hands-Free Lean-to-Steer Control
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Solution Overview
Problem
Existing robotic control systems lack an efficient method for estimating and utilizing torso dynamics of seated users to control physical or virtual robotic devices or avatars without the need for hand-based inputs.
Innovation Solution
The Torso-dynamics Estimation System (TES) measures leaning and twisting torso motions of seated users using instrumented seats, wearable sensors, and other sensing devices, converting these motions into control signals for robotic devices or avatars.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hand-based control interfaces are used for robotic devices, then control precision is improved, but user freedom and multitasking capability deteriorate
Solution Approach 1:
The patent replaces hand-based mechanical control interfaces with a torso-based control system that uses force sensing seats and inertial measurement units to detect torso dynamics. This substitution allows users to control robotic devices through natural torso movements while keeping their hands free for other tasks, thereby maintaining control precision while improving user freedom and multitasking capability.
2Ease of operation
If torso motion sensing is implemented for hands-free control, then user freedom is improved, but system complexity deteriorates
Solution Approach 1:
The patent employs force sensing seats and inertial measurement units that serve multiple functions: they detect both static weight distribution and dynamic torso movements, providing comprehensive control data from a single integrated system. This multi-functionality reduces the need for separate sensing components, thereby managing system complexity while enabling sophisticated hands-free control capabilities.
Solution Approach 2:
The patent introduces torso dynamics as an intermediary control mechanism between the user and the robotic device. By using torso movements as the control interface, the system mediates between the user's intent and the device's action, simplifying the control architecture compared to direct hand-based manipulation while maintaining intuitive control.
3Measurement precision
If multiple sensing devices are used to capture torso dynamics, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent combines force sensing seat technology with inertial measurement units to create an integrated torso dynamics sensing system. By merging these sensing modalities, the system achieves comprehensive and precise measurement of torso movements through weight distribution and acceleration data, while reducing the complexity that would arise from using entirely separate sensing systems.
Solution Approach 2:
The force sensing seats and inertial measurement units are designed to perform multiple measurement functions simultaneously, capturing both static and dynamic aspects of torso motion. This multi-functionality allows the system to achieve high measurement precision across different motion types without proportionally increasing system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
TES enables hands-free human-robot interaction by accurately translating torso motions into control signals, allowing users to control robotic devices or avatars with greater freedom and multitasking capabilities.
Implementation Method 1
a wearable sensor (e.g., inertial measurement unit, IMU)... to quantify the translational (e.g., leaning in all directions) and rotational (e.g., twisting) motions of the torso
Implementation Method 2
an instrumented seat (Force Sensing Seat, FSS)... based on orthogonal orientations of loadcells
Implementation Method 3
Another version is based on a Stewart-platform orientation... a Stewart-platform based FSS and wearable IMU is used for a lean-to-steer hands-free navigation
Data Source
AI summary
This application relates generally to robotic control/navigation and is specifically directed to a Torso-dynamics Estimation System (TES) for estimating leaning and twisting torso motions of a seated user and using such estimation or measurement signals to control movement of physical or virtual robotic devices or avatars solely using the user's upper body motion. For example, these signals can be used in lean-to-steer scenarios where the seated user is a rider/driver in a personal mobility device (e.g., powered chair or scooter), vehicle (e.g., car or drone), industrial equipment (e.g., excavator), or humanoid robot/avatar that could be in the physical or virtual worlds. Thus, TES offers a hands-free human-robot interaction for controlling a mobile device.