Robot Approach Trajectory Control for Socially Acceptable Human Interaction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robots designed for social interactions face challenges in approaching humans in a socially acceptable manner, as the shape of the trajectory can affect user comfort and acceptance, and existing approaches fail to account for cultural differences in social norms.
Innovation Solution
An inverse optimal control approach is implemented, where a robot's movement is controlled along a trajectory defined by a cost function that includes terms for duration, social force, lateral acceleration, angular acceleration, longitudinal acceleration, and centrifugal force reduction, with weights optimized in stages to mimic human-like movement and ensure socially compliant interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a robot uses a straight line approach to reach a human target, then the movement is simple and direct, but it may make the person feel uncomfortable and reduce social acceptance
Solution Approach 1:
The patent applies curvature to the robot's approach trajectory by introducing lateral motion components that create curved paths instead of straight lines. The cost function includes terms that penalize excessive curvature while allowing moderate curves that improve social acceptance. This transforms the rigid straight-line approach into a flexible curved trajectory that balances simplicity with social comfort.
Solution Approach 2:
The patent makes the trajectory dynamic by optimizing it in real-time based on the robot's current state and the human target's position. The cost function dynamically adjusts weights for different trajectory characteristics (curvature, acceleration, duration) depending on the situation. This allows the robot to adapt its approach style to different social contexts while maintaining operational simplicity.
2Adaptability or versatility
If a robot optimizes trajectory to improve social acceptance, then user comfort increases, but the computational complexity and control difficulty increase
Solution Approach 1:
The patent replaces complex mechanical trajectory planning with a mathematical optimization approach. Instead of using intricate control mechanisms to generate socially compliant paths, the system uses a cost function with multiple terms that encode social norms. The optimizer mathematically determines the optimal trajectory parameters, substituting mechanical complexity with computational elegance.
Solution Approach 2:
The patent manages control complexity by parameterizing the trajectory using a small set of key parameters (initial velocity, acceleration, curvature rates) rather than controlling every aspect of the motion independently. The cost function operates on these parameters, transforming a high-dimensional control problem into a lower-dimensional optimization problem that is computationally tractable while still achieving social compliance.
3Productivity
If a robot approaches a human target quickly, then the interaction initiation is efficient, but it may reduce safety and increase user discomfort
Solution Approach 1:
The patent uses parameter changes to balance speed and comfort by dynamically adjusting velocity and acceleration parameters throughout the approach. The cost function includes terms that penalize excessive acceleration and velocity near the target while allowing faster movement during the initial phase of approach. This creates a velocity profile that is efficient overall but comfortable locally, resolving the contradiction between productivity and user comfort.
4Adaptability or versatility
If a robot follows a curved trajectory to improve social acceptance, then user comfort increases, but the trajectory duration increases
Solution Approach 1:
The patent makes the trajectory duration dynamic rather than fixed. The optimizer determines the optimal duration as part of the solution, allowing it to adjust based on the desired curvature and speed profile. This dynamic duration optimization enables the system to find the sweet spot where the trajectory is curved enough to be socially acceptable but not so curved that it unnecessarily prolongs the approach, balancing social acceptance with efficiency.
Data Source
AI summary
A controller for an inverse optimal control approach robot may control movement of a robot body toward a human target along a trajectory according to a cost function. The cost function may include many terms. A first term may be associated with a duration of the trajectory for the robot. A second term may be associated with a social force and a final distance between the robot and the human target. A third term may be associated with a lateral acceleration for the robot. A fourth term may be associated with an angular acceleration for the robot. A fifth term may be associated with a longitudinal acceleration for the robot. A sixth term may be associated with a reduction of centrifugal force applied to the robot body.