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Automatic Processing and Automatic Social Behavior

Automatic Processing and Automatic Social Behavior

Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...

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Related Experiment Video

Updated: Apr 15, 2026

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

Trajectory Prediction-Enabled Self-Decision-Making for Autonomous Cleaning Robots in Semi-Structured Dynamic Campus

Jie Peng¹, Zhengze Zhu^1,2,3,4,5, Qingsong Fan⁶

¹School of Intelligent Connected Vehicle, Hubei University of Automotive Technology, Shiyan 442002, China.

Sensors (Basel, Switzerland)

|April 14, 2026

Summary

This summary is machine-generated.

Autonomous cleaning robots improve safety and efficiency by predicting the future movements of pedestrians and vehicles. This trajectory prediction framework enables robots to make smarter decisions, reducing abrupt movements in dynamic environments.

Keywords:

autonomous cleaning robots self-decision-making trajectory prediction

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

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Last Updated: Apr 15, 2026

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Area of Science:

Robotics
Artificial Intelligence
Computer Vision

Background:

Autonomous cleaning robots operate in complex, dynamic environments with diverse agents like pedestrians and vehicles.
Safe navigation requires anticipating surrounding agents' future movements beyond simple reactive obstacle avoidance.

Purpose of the Study:

To develop and evaluate a trajectory prediction-enabled self-decision-making framework for autonomous cleaning robots in campus environments.
To enhance robot decision-making by incorporating predictive models of agent behavior.

Main Methods:

A learning-based multi-agent trajectory prediction model was trained offline using benchmark and real-world data.
Predicted trajectories were integrated as priors into the robot's online decision-making and planning.
Evaluation was conducted on a high-fidelity simulation platform using data-driven scenario reconstruction.

Main Results:

The framework demonstrated improved motion stability and fewer abrupt adjustments in interaction scenarios.
Short-term prediction horizons achieved over 90% ADERate and FDERate.
Lane-change prediction accuracy reached approximately 79%, with stable speed tracking in medium-density traffic.

Conclusions:

Integrating trajectory prediction significantly enhances the stability and predictability of autonomous cleaning robot behavior.
The proposed framework offers a robust solution for safe and efficient robot operation in interaction-rich environments.