Semi-Autonomous Robot Control Model Updating From Candidate Actions
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Solution Overview
Problem
Current robotic systems face challenges in increasing the autonomy of semi-autonomous robots, as they often require significant human intervention to make decisions and adapt to changing environments, limiting their operational efficiency and applicability.
Innovation Solution
A method where a semi-autonomous robot identifies candidate actions based on detected events or conditions, collects ancillary data, and transmits requests to a tele-operation system for instructions, which analyzes the data to determine the likelihood of each action contributing to an objective, allowing the robot to update its control model and increase its autonomy level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a semi-autonomous robot operates with reduced human intervention, then operational efficiency is improved, but the robot's ability to make decisions and adapt to changing environments deteriorates
Solution Approach 1:
The system implements a feedback loop where the robot's control model is continuously updated based on tele-operated instructions and environmental data. The robot receives feedback from the tele-operation system about its candidate actions and uses this feedback to refine its decision-making algorithms, thereby improving both autonomy and adaptability simultaneously.
Solution Approach 2:
The robot autonomously generates candidate actions and evaluates them using its control model without requiring constant human intervention. It independently collects environmental data, scores potential actions based on expected progress toward objectives, and only seeks tele-operated assistance when unable to determine a suitable action, thus serving itself while maintaining adaptability.
2Extent of automation
If the robot autonomously evaluates and selects candidate actions, then autonomy level is improved, but the complexity of the control system increases
Solution Approach 1:
The control system is segmented into distinct functional modules: environmental sensing, candidate action generation, action scoring based on expected progress, and selection decision-making. This modular architecture allows the robot to achieve high autonomy while managing complexity through organized, separable components that can be independently developed and refined.
Solution Approach 2:
The system manages complexity by dynamically adjusting parameters such as the threshold for seeking tele-operated assistance and the weighting of different action scoring criteria. By changing these parameters, the robot can adapt its autonomy level and control complexity to match task requirements without redesigning the entire control system.
3Measurement precision
If the robot collects and analyzes extensive ancillary data for each candidate action, then decision accuracy is improved, but the time and computational resources required increase
Solution Approach 1:
The robot collects only the necessary ancillary data required to evaluate candidate actions adequately, rather than gathering all possible data. It focuses on collecting environmental sensor data directly relevant to the current task and candidate actions, thereby achieving sufficient decision accuracy without excessive time or computational resource expenditure.
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.