EcoSwarm – Collective Intelligence for Energy Optimization in Mobile Robotics
The primary objective of the EcoSwarm project is to improve energy efficiency in autonomous mobile robotic systems through the application of collective intelligence and optimization
algorithms. The project aims to develop a universal swarm robotics system in which robots operate in a coordinated manner to reduce energy consumption. This will be achieved using digital twins, reinforcement learning techniques, and intelligent optimization to enhance realtime decision-making.
[vc_row type="in_container" full_screen_row_position="middle" column_margin="default" column_direction="default" column_direction_tablet="default" column_direction_phone="default" scene_position="center" text_color="dark" text_align="left" row_border_radius="none" row_border_radius_applies="bg" overflow="visible" overlay_strength="0.3" gradient_direction="left_to_right" shape_divider_position="bottom" bg_image_animation="none"][vc_column column_padding="no-extra-padding" column_padding_tablet="inherit" column_padding_phone="inherit" column_padding_position="all" column_element_direction_desktop="default" column_element_spacing="default" desktop_text_alignment="default" tablet_text_alignment="default" phone_text_alignment="default" background_color_opacity="1" background_hover_color_opacity="1" column_backdrop_filter="none" column_shadow="none" column_border_radius="none" column_link_target="_self" column_position="default" gradient_direction="left_to_right" overlay_strength="0.3" width="1/1" tablet_width_inherit="default" animation_type="default" bg_image_animation="none" border_type="simple" column_border_width="none" column_border_style="solid"][vc_column_text]EcoSwarm is an innovative initiative addressing the challenge of energy consumption in autonomous mobile robotics—a critical factor in the automation of productive environments. The project explores the use of collective intelligence and advanced algorithms to optimize robotic energy efficiency, enabling coordinated and sustainable operations. NAIR Center collaborates with organizations such as Aldakin, Tedcas, Dateando, Perfinasa, and the Public University of Navarre (UPNA).
The project is part of the 2024–2027 Strategic R&D Projects and aligns with digital innovation goals in strategic sectors.
Nair’s contributions include:
• Development of digital twins to model and predict robot behavior
• Implementation of reinforcement learning and intelligent optimization techniques
• Coordination and optimization of navigation strategies in robotic swarms
• Validation and testing in productive environments
Timeline
April 2024 – December 2026
Partners:
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The project is part of the 2024–2027 Strategic R&D Projects and aligns with digital innovation goals in strategic sectors.
Nair’s contributions include:
• Development of digital twins to model and predict robot behavior
• Implementation of reinforcement learning and intelligent optimization techniques
• Coordination and optimization of navigation strategies in robotic swarms
• Validation and testing in productive environments
Timeline
April 2024 – December 2026
Partners:
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