Full Papers
Original research contributions with substantial technical depth and experimental validation.
Machine Learning/CORE Unranked
IROS 2026
Hybrid Architectures for Embodied Autonomy: Bridging Learning, Planning, and Control
The IROS 2026 workshop 'Hybrid Architectures for Autonomy' (BLPC 2026) focuses on advancing hybrid architectures that integrate symbolic reasoning, learning-based methods, and traditional control systems to enable robust and interpretable autonomy in robotics. It invites research that bridges the gap between AI and robotics, emphasizing safety, verification, and real-world applicability.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short Papers
Preliminary results, system demos, or position papers with clear insight or novelty.
Journal-First Papers
Extended versions of recently published journal articles that present new insights or expanded evaluations.
Research areas in scope
01
Topics of Interest
Hybrid architectures for robotic autonomySymbolic reasoning and planning in roboticsLearning-based methods for autonomyVerification and validation of hybrid systemsIntegration of AI and control theoryInterpretable and explainable autonomous systemsSafe and reliable decision-making under uncertaintyReal-world deployment of hybrid robotic systems
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Full papers are limited to 8 pages, short papers to 4 pages, and journal-first papers to 6 pages, all in IEEE format.
- Dual submission to other conferences or journals is not permitted during review.
- Author lists and affiliations may be updated after acceptance but not during the review process.
- Authors must include a statement on the use of AI tools in the preparation of the submission.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026