[{"publication_status":"accepted","date_created":"2026-09-21T16:34:09Z","date_updated":"2026-09-21T19:31:42Z","status":"public","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Deep reinforcement learning (RL) policies for robotic control typically overfit to a single hardware configuration. Any change to the kinematic chain breaks the learned mapping and requires complete retraining. This paper investigates whether combining self-attention mechanisms with explicit spatial observations can improve a policy’s adaptability to varying kinematic topologies. We train a single RL agent to control a robotic manipulator across different degrees of freedom (DOF), ranging from a restricted 4-DOF mode to a fully redundant 7-DOF configuration. Instead of fixed-length state vectors, the method processes the active joints as a variable-length sequence in an attention buffer, enriching each joint’s representation with its relative spatial routing and geometric Jacobian influence. This structure allows the agent to dynamically evaluate the physical utility of its available actuators. The proposed Architecture reaches a success rate of 82.1% across trained topologies and 66.6% on unseen configurations, outperforming MLP and generic attention baselines while remaining nearly collisionfree. Finally, we demonstrate successful sim-to-real transfer by deploying the simulation-trained agent on a physical Franka Emika Panda manipulator."}],"user_id":"244831","citation":{"chicago":"Mayer, Patrick Thomas, and Jan Rexilius. “Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control,” n.d.","apa":"Mayer, P. T., &#38; Rexilius, J. (n.d.). Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control. Presented at the 9th Iberian Robotics Conference (ROBOT) , Barcelona.","ama":"Mayer PT, Rexilius J. Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control.","bibtex":"@inproceedings{Mayer_Rexilius, title={Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control}, author={Mayer, Patrick Thomas and Rexilius, Jan} }","short":"P.T. Mayer, J. Rexilius, in: n.d.","mla":"Mayer, Patrick Thomas, and Jan Rexilius. <i>Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control</i>.","ieee":"P. T. Mayer and J. Rexilius, “Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control,” presented at the 9th Iberian Robotics Conference (ROBOT) , Barcelona.","alphadin":"<span style=\"font-variant:small-caps;\">Mayer, Patrick Thomas</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control. In:"},"_id":"7175","author":[{"id":"244831","first_name":"Patrick Thomas","last_name":"Mayer","orcid":"0009-0009-6800-1273","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0009-6800-1273/work/227375532","full_name":"Mayer, Patrick Thomas"},{"id":"245736","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/227375533","full_name":"Rexilius, Jan","first_name":"Jan","orcid":"0000-0002-4579-214X","last_name":"Rexilius"}],"department":[{"_id":"102"}],"year":"2026","type":"conference","conference":{"location":"Barcelona","name":"9th Iberian Robotics Conference (ROBOT) ","end_date":"2026-11-20","start_date":"2026-11-18"},"title":"Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control","project":[{"_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D","name":"Institute for Building Intelligence"}],"quality_controlled":"1","keyword":["Reinforcement Learning","Robotic Manipulation","Morphology Generalization","Sim-to-Real Transfer"]},{"year":"2026","type":"conference","conference":{"start_date":"2026-10-27","end_date":"2026-10-30","location":"Sapporo","name":"26th International Conference on Control, Automation and Systems (ICCAS)"},"title":"A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer","quality_controlled":"1","project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}],"keyword":["Reinforcement Learning","Hybrid Control","Sim-to-Real","Robotic Manipulation","Inverse Kinematics."],"date_updated":"2026-09-21T19:31:37Z","status":"public","publication_status":"accepted","date_created":"2026-09-21T16:30:06Z","user_id":"244831","abstract":[{"lang":"eng","text":"This paper presents a hybrid control architecture for dynamic robotic picking tasks. The framework combines a Deep Reinforcement Learning policy for high-level interception with a dedicated Inverse Kinematics controller for precise terminal grasping, while mitigating precision limitations of monolithic learning-based approaches. The framework utilizes a Proximal Policy Optimization agent to approach moving targets, seamlessly transitioning to an Inverse Kinematics solver that reduces terminal orientational and positional errors while minimizing cumulative control effort. To facilitate deployment on physical hardware, a robust sim-to-real pipeline incorporating system identification, domain randomization, and latency injection is employed. Experimental results on a physical Franka Emika Panda manipulator validate this hybrid architecture. The system achieves an 80% success rate in pick-and-place tasks, compared to 60.8% for unadapted baselines, with no safety-critical violations such as joint limit breaches or collisions observed during testing."}],"language":[{"iso":"eng"}],"_id":"7174","citation":{"ama":"Mayer PT, Rexilius J. A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer.","bibtex":"@inproceedings{Mayer_Rexilius, title={A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer}, author={Mayer, Patrick Thomas and Rexilius, Jan} }","ieee":"P. T. Mayer and J. Rexilius, “A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer,” presented at the 26th International Conference on Control, Automation and Systems (ICCAS), Sapporo.","mla":"Mayer, Patrick Thomas, and Jan Rexilius. <i>A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer</i>.","alphadin":"<span style=\"font-variant:small-caps;\">Mayer, Patrick Thomas</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer. In:","short":"P.T. Mayer, J. Rexilius, in: n.d.","apa":"Mayer, P. T., &#38; Rexilius, J. (n.d.). A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer. 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(n.d.). Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints. Presented at the 9th Iberian Robotics Conference (ROBOT), Barcelona.","chicago":"Kirsch, André, and Jan Rexilius. “Reinforcement Learning-Based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints,” n.d.","alphadin":"<span style=\"font-variant:small-caps;\">Kirsch, André</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints. In:","mla":"Kirsch, André, and Jan Rexilius. <i>Reinforcement Learning-Based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints</i>.","ieee":"A. Kirsch and J. Rexilius, “Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints,” presented at the 9th Iberian Robotics Conference (ROBOT), Barcelona.","short":"A. Kirsch, J. Rexilius, in: n.d.","bibtex":"@inproceedings{Kirsch_Rexilius, title={Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints}, author={Kirsch, André and Rexilius, Jan} }","ama":"Kirsch A, Rexilius J. Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints."},"_id":"7173","author":[{"first_name":"André","last_name":"Kirsch","full_name":"Kirsch, André","id":"229807"},{"id":"245736","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/227345663","full_name":"Rexilius, Jan","first_name":"Jan","last_name":"Rexilius","orcid":"0000-0002-4579-214X"}],"publication_status":"accepted","date_created":"2026-09-21T14:31:38Z","date_updated":"2026-09-21T14:33:10Z","status":"public","abstract":[{"text":"Reinforcement learning has achieved state-of-the-art performance in MAV control, waypoint flight, and obstacle avoidance. However, existing RL approaches often assume fixed objectives and constraints, with flight behavior largely limited by vehicle dynamics and orientation considered only when required for locomotion. Classical planning and model predictive control handle such constraints explicitly, but require optimization or replanning. This motivates methods that combine learned local control with explicit constraint handling. We combine reinforcement learning with control barrier functions to improve constraint-aware execution. We propose parameterized waypoints that encode orientation, velocity, and corridor constraints. Simulation and real-world experiments show that a single policy can execute different constraint-parameterized navigation scenarios, revealing scenario-dependent trade-offs between traversal time, tracking accuracy, and constraint satisfaction.","lang":"eng"}],"language":[{"iso":"eng"}],"user_id":"229807"},{"keyword":["Waste monitoring","Waste level estimation","MAV navigation"],"project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}],"quality_controlled":"1","title":"Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle","related_material":{"record":[{"id":"6993","relation":"other","status":"public"}]},"conference":{"start_date":"2026-06-15","location":"Lissabon, Portugal","name":"22nd International Conference on Intelligent Environments (IE)","end_date":"2026-06-18"},"doi":"10.1109/IE69249.2026.11539031","type":"conference","year":"2026","department":[{"_id":"102"}],"author":[{"id":"229807","full_name":"Kirsch, André","first_name":"André","last_name":"Kirsch"},{"id":"245736","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/208820721","full_name":"Rexilius, Jan","first_name":"Jan","orcid":"0000-0002-4579-214X","last_name":"Rexilius"}],"main_file_link":[{"url":"https://ieeexplore.ieee.org/document/11539031"}],"_id":"6790","citation":{"short":"A. Kirsch, J. Rexilius, in: 2026.","alphadin":"<span style=\"font-variant:small-caps;\">Kirsch, André</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle. In: , 2026","ieee":"A. Kirsch and J. Rexilius, “Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle,” presented at the 22nd International Conference on Intelligent Environments (IE), Lissabon, Portugal, 2026.","mla":"Kirsch, André, and Jan Rexilius. <i>Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle</i>. 2026, doi:<a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">10.1109/IE69249.2026.11539031</a>.","bibtex":"@inproceedings{Kirsch_Rexilius_2026, title={Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle}, DOI={<a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">10.1109/IE69249.2026.11539031</a>}, author={Kirsch, André and Rexilius, Jan}, year={2026} }","ama":"Kirsch A, Rexilius J. Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle. In: ; 2026. doi:<a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">10.1109/IE69249.2026.11539031</a>","chicago":"Kirsch, André, and Jan Rexilius. “Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle,” 2026. <a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">https://doi.org/10.1109/IE69249.2026.11539031</a>.","apa":"Kirsch, A., &#38; Rexilius, J. (2026). Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle. Presented at the 22nd International Conference on Intelligent Environments (IE), Lissabon, Portugal. <a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">https://doi.org/10.1109/IE69249.2026.11539031</a>"},"user_id":"220548","language":[{"iso":"eng"}],"status":"public","date_updated":"2026-06-23T06:50:04Z","date_created":"2026-03-06T12:30:43Z","publication_status":"published"},{"date_created":"2026-06-16T10:10:28Z","year":"2026","status":"public","date_updated":"2026-06-23T06:50:04Z","publisher":"Hochschule Bielefeld","type":"research_data","user_id":"220548","citation":{"ama":"Kirsch A, Rexilius J. <i>Waste Bin Dataset </i>. Hochschule Bielefeld; 2026.","bibtex":"@book{Kirsch_Rexilius_2026, title={Waste Bin Dataset }, publisher={Hochschule Bielefeld}, author={Kirsch, André and Rexilius, Jan}, year={2026} }","mla":"Kirsch, André, and Jan Rexilius. <i>Waste Bin Dataset </i>. Hochschule Bielefeld, 2026.","ieee":"A. Kirsch and J. Rexilius, <i>Waste Bin Dataset </i>. Hochschule Bielefeld, 2026.","alphadin":"<span style=\"font-variant:small-caps;\">Kirsch, André</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: <i>Waste Bin Dataset </i> : Hochschule Bielefeld, 2026","short":"A. Kirsch, J. Rexilius, Waste Bin Dataset , Hochschule Bielefeld, 2026.","chicago":"Kirsch, André, and Jan Rexilius. <i>Waste Bin Dataset </i>. Hochschule Bielefeld, 2026.","apa":"Kirsch, A., &#38; Rexilius, J. (2026). <i>Waste Bin Dataset </i>. Hochschule Bielefeld."},"_id":"6993","related_material":{"link":[{"url":"https://huggingface.co/datasets/akirsch1/waste-bin-dataset","relation":"research_data"}],"record":[{"id":"6790","status":"public","relation":"other"}]},"author":[{"id":"229807","full_name":"Kirsch, André","first_name":"André","last_name":"Kirsch"},{"id":"245736","first_name":"Jan","last_name":"Rexilius","orcid":"0000-0002-4579-214X","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/217902787","full_name":"Rexilius, Jan"}],"title":"Waste Bin Dataset ","project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}]},{"language":[{"iso":"eng"}],"user_id":"229000","date_created":"2026-06-03T09:06:55Z","status":"public","date_updated":"2026-06-10T08:00:19Z","publication":"IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","author":[{"full_name":"Riechmann-Thom, Malte","first_name":"Malte","last_name":"Riechmann-Thom","id":"229000"},{"id":"245736","orcid":"0000-0002-4579-214X","last_name":"Rexilius","first_name":"Jan","full_name":"Rexilius, Jan","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/216598627"}],"citation":{"apa":"Riechmann-Thom, M., &#38; Rexilius, J. (2026). Multi-Perspective AR Interaction Through Robot Viewpoint Control. In <i>IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)</i>. Kitakyushu.","chicago":"Riechmann-Thom, Malte, and Jan Rexilius. “Multi-Perspective AR Interaction Through Robot Viewpoint Control.” In <i>IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)</i>, 2026.","bibtex":"@inproceedings{Riechmann-Thom_Rexilius_2026, title={Multi-Perspective AR Interaction Through Robot Viewpoint Control}, booktitle={IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)}, author={Riechmann-Thom, Malte and Rexilius, Jan}, year={2026} }","ama":"Riechmann-Thom M, Rexilius J. Multi-Perspective AR Interaction Through Robot Viewpoint Control. In: <i>IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)</i>. ; 2026.","short":"M. Riechmann-Thom, J. 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Visualizing Motion Intent in Heterogeneous Multi-Robot Environments. In: <i>IEEE International Symposium on Mixed and Augmented Reality (ISMAR)</i>. ; 2025. doi:<a href=\"https://doi.org/10.1109/ISMAR-Adjunct68609.2025.00145\">10.1109/ISMAR-Adjunct68609.2025.00145</a>","bibtex":"@inproceedings{Riechmann-Thom_Rexilius_2025, title={Visualizing Motion Intent in Heterogeneous Multi-Robot Environments}, DOI={<a href=\"https://doi.org/10.1109/ISMAR-Adjunct68609.2025.00145\">10.1109/ISMAR-Adjunct68609.2025.00145</a>}, booktitle={IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, author={Riechmann-Thom, Malte and Rexilius, Jan}, year={2025} }","short":"M. Riechmann-Thom, J. Rexilius, in: IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2025.","mla":"Riechmann-Thom, Malte, and Jan Rexilius. “Visualizing Motion Intent in Heterogeneous Multi-Robot Environments.” <i>IEEE International Symposium on Mixed and Augmented Reality (ISMAR)</i>, 2025, doi:<a href=\"https://doi.org/10.1109/ISMAR-Adjunct68609.2025.00145\">10.1109/ISMAR-Adjunct68609.2025.00145</a>.","ieee":"M. Riechmann-Thom and J. Rexilius, “Visualizing Motion Intent in Heterogeneous Multi-Robot Environments,” in <i>IEEE International Symposium on Mixed and Augmented Reality (ISMAR)</i>, Daejeon, South Korea, 2025.","alphadin":"<span style=\"font-variant:small-caps;\">Riechmann-Thom, Malte</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: Visualizing Motion Intent in Heterogeneous Multi-Robot Environments. 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Daejeon, South Korea. <a href=\"https://doi.org/10.1109/ISMAR-Adjunct68609.2025.00145\">https://doi.org/10.1109/ISMAR-Adjunct68609.2025.00145</a>"},"author":[{"id":"229000","full_name":"Riechmann-Thom, Malte","first_name":"Malte","last_name":"Riechmann-Thom"},{"id":"245736","full_name":"Rexilius, Jan","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/191981952","last_name":"Rexilius","orcid":"0000-0002-4579-214X","first_name":"Jan"}],"year":"2025","type":"conference","doi":"10.1109/ISMAR-Adjunct68609.2025.00145","conference":{"start_date":"2025-10-08","end_date":"2025-10-12","location":"Daejeon, South Korea","name":"IEEE International Symposium on Mixed and Augmented Reality (ISMAR)"},"project":[{"_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D","name":"Institute for Building Intelligence"}],"quality_controlled":"1","title":"Visualizing Motion Intent in Heterogeneous Multi-Robot Environments"},{"quality_controlled":"1","project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}],"title":"A State-Aware Ant Colony Optimization Approach to the Roll-on/Roll-off Problem for Skip Loaders","urn":"urn:nbn:de:hbz:bi10-60270","oa":"1","file_date_updated":"2025-06-27T17:25:24Z","conference":{"start_date":"2025-06-03","name":"KI-Kongress","location":"Bielefeld","end_date":"2025-06-03"},"publisher":"Schriftenreihe des Institus for Data Science Solutions","type":"conference","has_accepted_license":"1","file":[{"file_size":34739,"file_id":"6028","file_name":"A_State_Aware_Ant_Colony_Optimization_Approach_To_The_Roll_On_Roll_Off_Problem_For_Skip_Loaders.pdf","relation":"main_file","content_type":"application/pdf","date_updated":"2025-06-27T17:25:24Z","creator":"ldeutsch","success":1,"access_level":"open_access","date_created":"2025-06-27T17:25:24Z"}],"year":"2025","author":[{"id":"229002","first_name":"Luis","last_name":"Deutsch","full_name":"Deutsch, Luis"},{"id":"213498","first_name":"Matthias","last_name":"König","orcid":"0000-0002-4915-0750","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4915-0750/work/187881446","full_name":"König, Matthias"},{"id":"245736","full_name":"Rexilius, Jan","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/187881447","last_name":"Rexilius","orcid":"0000-0002-4579-214X","first_name":"Jan"}],"department":[{"_id":"102"}],"_id":"6027","citation":{"apa":"Deutsch, L., König, M., &#38; Rexilius, J. 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