Robot Autonomy Control With Tele-Operation Guidance
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Solution Overview
Problem
Existing robotic systems face challenges in achieving semi-autonomous operation, particularly in selecting appropriate actions without human intervention, especially when encountering uncertain or dynamic environments.
Innovation Solution
The method involves identifying a set of candidate actions, collecting ancillary data for each action, and transmitting a request for instructions to a tele-operation system. The robot then receives instructions, executes them, and updates its control model to increase its level of autonomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot operates autonomously without human intervention, then operational efficiency is improved, but reliability deteriorates due to inability to handle uncertain or dynamic environments
Solution Approach 1:
The patent introduces a tele-operation system as an intermediary between the robot and human operators. The robot autonomously identifies candidate actions and collects ancillary data, then transmits this information to the tele-operation system which provides guidance or approval. This intermediary system enables the robot to operate semi-autonomously, improving efficiency while maintaining reliability through human oversight when needed.
2Reliability
If the robot transmits requests for instructions to a tele-operation system, then reliability is improved through human guidance, but productivity deteriorates due to reduced autonomy
Solution Approach 1:
The patent implements partial autonomy where the robot independently performs action identification and data collection, then selectively requests guidance only when needed. The robot scores candidate actions based on expected progress toward objectives and can autonomously execute high-probability actions without tele-operation intervention. This partial action approach maintains reliability through selective human guidance while preserving productivity through autonomous operation for routine decisions.
3Adaptability or versatility
If the robot updates its control model frequently, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the robot's control model is updated based on outcomes of executed actions and new information from the environment. The control model uses this feedback to improve future action selection and scoring. This feedback-based update approach enables the robot to adapt to changing conditions and learn from experience while maintaining a manageable control architecture that processes information incrementally rather than requiring complete system redesign.
Data Source
AI summary
In a method of operation of a robot, the robot identifies a set of candidate actions that may be performed by the robot, and collects, for each candidate action of the set of candidate actions, a respective set of ancillary data. The robot transmits a request for instructions to a tele-operation system that is communicatively coupled to the robot. The request for instructions includes each candidate action and each respective set of ancillary data. The robot receives, and executes, the instructions from the tele-operation system. The robot updates a control model, based at least in part on each candidate action, each respective set of ancillary data, and the instructions, to increase a level of autonomy of the robot. The robot may transmit the request for instructions to the tele-operation system in response to determining the robot is unable to select a candidate action to perform in furtherance of an objective.