Manual, Semi or Fully Autonomous Flipper Control? A Framework for Fair Comparison

2025-03-18

AI Summary

This study addresses the fair comparative evaluation of manual, semi-autonomous, and fully autonomous control strategies for tracked skid-steer bucket robots, focusing on the trade-off between operator cognitive load and traversal quality. Method: We introduce the first Quality-Load two-dimensional assessment space; develop a unified, interface-encapsulated framework for reproducible control strategy implementation; design a cognitive load quantification model integrating physiological and behavioral data; formulate a Traversal Quality evaluation function; and build a benchmarked, data-driven assessment map generation tool. A novel semi-autonomous control strategy is proposed to jointly optimize operational burden and task performance. Results: Experiments demonstrate that experienced operators achieve high efficiency with 6-DOF continuous manual control under third-person perspective; the new semi-autonomous strategy significantly narrows the performance gap between autonomous and manual control; all methods are validated comparably on real hardware; and the project open-sources a standardized benchmark interface to enable cross-method, reproducible evaluation.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

We investigated the performance of existing semi- and fully autonomous methods for controlling flipper-based skid-steer robots. Our study involves reimplementation of these methods for fair comparison and it introduces a novel semi-autonomous control policy that provides a compelling trade-off among current state-of-the-art approaches. We also propose new metrics for assessing cognitive load and traversal quality and offer a benchmarking interface for generating Quality-Load graphs from recorded data. Our results, presented in a 2D Quality-Load space, demonstrate that the new control policy effectively bridges the gap between autonomous and manual control methods. Additionally, we reveal a surprising fact that fully manual, continuous control of all six degrees of freedom remains highly effective when performed by an experienced operator on a well-designed analog controller from third person view.

Problem

• Compare semi- and fully autonomous flipper control methods.
• Introduce a novel semi-autonomous control policy.
• Propose metrics for cognitive load and traversal quality.

Innovation

• Novel semi-autonomous control policy introduced
• New metrics for cognitive load and traversal quality
• Benchmarking interface for Quality-Load graphs