{"id":12047,"date":"2026-08-19T14:20:30","date_gmt":"2026-08-19T14:20:30","guid":{"rendered":"https:\/\/cyber-valley.de\/?post_type=researchfund-project&#038;p=12047"},"modified":"2026-09-01T12:08:17","modified_gmt":"2026-09-01T12:08:17","slug":"x_task-and-motion-planning-for-collaborative-robotic-construction-with-irregular-materials","status":"publish","type":"researchfund-project","link":"https:\/\/cyber-valley.de\/de\/researchfund-project\/x_task-and-motion-planning-for-collaborative-robotic-construction-with-irregular-materials\/","title":{"rendered":"Task and Motion Planning for Collaborative Robotic Construction with Irregular Materials"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Overview<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Construction is responsible for a large share of global carbon emissions, partly because it relies heavily on energy-intensive materials such as steel and concrete. Bamboo, by contrast, is a fast-growing, renewable material with high strength-to-weight ratio, but its natural variability and flexibility make it difficult to use in automated construction.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Led by Nicolas Kubail Kalousdian and Achim Menges at the Institute for Computational Design and Construction (ICD), University of Stuttgart, this project developed a robotic system for constructing with bamboo. The project ran from 2021 to 2024 and was funded by the Cyber\u00a0Valley Research Fund.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Key results<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Designed and implemented a custom mobile robotic system optimised for handling and assembling bamboo elements.<\/li>\n\n\n\n<li>Developed a hybrid <strong>task and motion planning (TAMP)<\/strong> approach that combines reinforcement learning with logic-geometric programming. Reinforcement learning enabled dynamic adaptation during bending tasks, while logic-geometric programming supported structured, multi-step planning of construction sequences.<\/li>\n\n\n\n<li>Created a high-fidelity simulation environment to model bamboo\u2019s mechanical behaviour and train reinforcement-learning policies before deployment on real hardware.<\/li>\n\n\n\n<li>Used domain randomisation and curriculum learning to improve transfer from simulation to reality, enabling the robot to work reliably with real, non-standardised bamboo.<\/li>\n\n\n\n<li>Demonstrated that the robotic system could reach, transport, and assemble bamboo elements, including cooperative behaviours between multiple robots.<\/li>\n\n\n\n<li>Built a full-scale architectural demonstrator that executed key construction tasks, showing the feasibility of robotic bamboo construction despite remaining engineering challenges.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Why it matters<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The project shows how AI and robotics can enable the use of renewable, low-carbon materials in construction. By automating the handling of flexible, non-standardised elements such as bamboo, it opens a pathway to more sustainable building practices that reduce dependence on carbon-intensive materials. The methods developed for task and motion planning, simulation-to-reality transfer, and multi-robot cooperation may also inform other forms of robotic construction and fabrication. <\/p>\n\n\n\n<h4 class=\"wp-block-heading\">This project produced the following peer-reviewed publications:&nbsp;<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>N. K. Kalousdian et al., \u201cLearning Robotic Manipulation of Natural Materials With\u00a0Variable Properties for Construction Tasks\u201d. In: IEEE Robotics and Automation Letters, Vol. 7, No. 2, April 2022, pp. 5749-5756.\u00a0<a href=\"https:\/\/ieeexplore.ieee.org\/document\/9735376\" target=\"_blank\" rel=\"noreferrer noopener\">DOI: 10.1109\/LRA.2022.3159288<\/a>.<\/li>\n<\/ul>\n","protected":false},"featured_media":0,"parent":0,"template":"","meta":{"_acf_changed":true},"cv-tag":[],"user-group":[],"class_list":["post-12047","researchfund-project","type-researchfund-project","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Task and Motion Planning for Collaborative Robotic Construction with Irregular Materials - Cyber Valley<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cyber-valley.de\/de\/researchfund-project\/x_task-and-motion-planning-for-collaborative-robotic-construction-with-irregular-materials\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Task and Motion Planning for Collaborative Robotic Construction with Irregular Materials - Cyber Valley\" \/>\n<meta property=\"og:description\" content=\"Overview Construction is responsible for a large share of global carbon emissions, partly because it relies heavily on energy-intensive materials such as steel and concrete. Bamboo, by contrast, is a fast-growing, renewable material with high strength-to-weight ratio, but its natural variability and flexibility make it difficult to use in automated construction. 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