Hybrid Conferencee

International Conference on Autonomous Robotics using Machine Learning (ICARML - 26)

7th - 8th September 2026 | Dubai, UAE

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Certificate of Presentation:
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Networking with Global Experts:
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Keynote Speaker Sessions:
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Best Paper & Best Paper Presentation Award:
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SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 4
SDG 4 Quality Education
SDG 8
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

Advancements in Reinforcement Learning for Robotics

This track focuses on the latest developments in reinforcement learning techniques and their applications in autonomous robotics. Researchers are invited to present novel algorithms and frameworks that enhance robot learning and decision-making capabilities.

Track 02

Path Planning and Motion Control Strategies

This session addresses innovative approaches to path planning and motion control in dynamic environments. Contributions should explore algorithms that improve navigation efficiency and obstacle avoidance in autonomous systems.

Track 03

Sensor Fusion Techniques for Enhanced Perception

This track highlights the integration of multiple sensor modalities to improve robot perception and situational awareness. Papers should discuss methodologies that enhance data interpretation and environmental understanding.

Track 04

Modeling and Predictive Analytics in Robotics

This session invites research on modeling techniques and predictive analytics that inform robotic behavior and decision-making. Contributions should demonstrate how predictive models can optimize robot performance in various tasks.

Track 05

Supervised and Unsupervised Learning in Robot Development

This track explores the application of supervised and unsupervised learning methods in the development of autonomous robots. Researchers are encouraged to share insights on training paradigms that enhance robot capabilities.

Track 06

Deep Learning Innovations for Autonomous Systems

This session focuses on the application of deep learning techniques to solve complex problems in autonomous robotics. Papers should present novel architectures or applications that push the boundaries of robot intelligence.

Track 07

Anomaly Detection in Robotic Systems

This track examines methods for detecting anomalies in robotic operations and environments. Contributions should highlight techniques that ensure reliability and safety in autonomous systems.

Track 08

Human-Robot Interaction and Collaboration

This session investigates the dynamics of human-robot interaction and collaborative systems. Papers should explore frameworks that enhance communication and cooperation between humans and robots.

Track 09

Adaptive Control Mechanisms for Robotics

This track focuses on adaptive control strategies that enable robots to adjust their behavior in response to changing environments. Contributions should demonstrate the effectiveness of adaptive techniques in real-world applications.

Track 10

Multi-Agent Systems and Coordination in Robotics

This session addresses the challenges and solutions in multi-agent systems for autonomous robotics. Researchers are invited to present strategies for coordination, communication, and task allocation among multiple robots.

Track 11

Optimization Techniques in Robotic Applications

This track explores optimization methodologies that enhance the performance and efficiency of robotic systems. Contributions should focus on algorithms that improve resource allocation and operational effectiveness in robotics.