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ORCIDAnastasios M. Lekkas
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2020 – today
- 2024
[c15]Camilla Fruzzetti, Michele Martelli, Anastasios M. Lekkas, Roger Skjetne, Morten Breivik:
Model-Based Motion Control Design for the Milliampere1 Prototype Ferry. ECC 2024: 3636-3643- [c14]Sindre Benjamin Remman, Anastasios M. Lekkas:
Using Shapley Additive Explanations to Explain a Deep Reinforcement Learning Agent Controlling a Turtlebot3 for Autonomous Navigation. ICINCO (1) 2024: 334-340 - [c13]Kristoffer Eikså, Jan Erlend Vatne, Anastasios M. Lekkas:
Explaining Deep Reinforcement Learning Policies with SHAP, Decision Trees, and Prototypes. MED 2024: 700-705 - [c12]Sindre Benjamin Remman, Bjørn Andreas Kristiansen, Anastasios M. Lekkas:
Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective. MED 2024: 718-723 - [c11]M. A. Hinostroza, Anastasios M. Lekkas, Aksel Andreas Transeth, Bjørnar Luteberget, Christian de Jonge, Svein Ivar Sagatun:
Autonomous Inspection and Maintenance Operations employing Multi-Robots: Preliminary Results. MESA 2024: 1-8 - [i16]Sindre Benjamin Remman, Anastasios M. Lekkas:
Discovering Behavioral Modes in Deep Reinforcement Learning Policies Using Trajectory Clustering in Latent Space. CoRR abs/2402.12939 (2024) - [i15]Sindre Benjamin Remman, Bjørn Andreas Kristiansen, Anastasios M. Lekkas:
Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective. CoRR abs/2406.01178 (2024) - 2023
- [j9]Simon J. N. Simonlexau
, Morten Breivik, Anastasios M. Lekkas:
Automated Docking for Marine Surface Vessels - A Survey. IEEE Access 11: 132324-132367 (2023) - [j8]Vilde B. Gjærum, Inga Strümke, Jakob Løver, Timothy Miller, Anastasios M. Lekkas:
Model tree methods for explaining deep reinforcement learning agents in real-time robotic applications. Neurocomputing 515: 133-144 (2023) - 2022
- [j7]Andreas B. Martinsen, Anastasios M. Lekkas, Sébastien Gros:
Optimal Model-Based Trajectory Planning With Static Polygonal Constraints. IEEE Trans. Control. Syst. Technol. 30(3): 1159-1170 (2022) - [c10]Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas:
Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning. ACC 2022: 2683-2690 - [i14]Vilde B. Gjærum, Inga Strümke, Ole Andreas Alsos, Anastasios M. Lekkas:
Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization. CoRR abs/2203.00368 (2022) - [i13]Vilde B. Gjærum, Ella-Lovise H. Rørvik, Anastasios M. Lekkas:
Approximating a deep reinforcement learning docking agent using linear model trees. CoRR abs/2203.00369 (2022) - [i12]Vilde B. Gjærum, Inga Strümke, Anastasios M. Lekkas, Tim Miller:
Real-Time Counterfactual Explanations For Robotic Systems With Multiple Continuous Outputs. CoRR abs/2212.04212 (2022) - 2021
- [j6]Andreas B. Martinsen, Anastasios M. Lekkas:
Two Space-Time Obstacle Representations Based on Ellipsoids and Polytopes. IEEE Access 9: 111152-111161 (2021) - [c9]Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas, Sébastien Gros:
Reinforcement Learning based on Scenario-tree MPC for ASVs. ACC 2021: 1985-1990 - [c8]Wenqi Cai, Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas, Sébastien Gros:
MPC-based Reinforcement Learning for a Simplified Freight Mission of Autonomous Surface Vehicles. CDC 2021: 2990-2995 - [c7]Sindre Benjamin Remman, Anastasios M. Lekkas:
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations. ECC 2021: 586-593 - [c6]Vilde B. Gjærum, Ella-Lovise H. Rørvik, Anastasios M. Lekkas:
Approximating a deep reinforcement learning docking agent using linear model trees. ECC 2021: 1465-1471 - [c5]Glenn Bitar, Bjørn-Olav H. Eriksen, Anastasios M. Lekkas, Morten Breivik:
Three-Phase Automatic Crossing for a Passenger Ferry With Field Trials. ECC 2021: 2271-2277 - [i11]Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas, Sébastien Gros:
Reinforcement Learning based on Scenario-tree MPC for ASVs. CoRR abs/2103.11949 (2021) - [i10]Wenqi Cai, Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas, Sebastien Gros:
MPC-based Reinforcement Learning for a Simplified Freight Mission of Autonomous Surface Vehicles. CoRR abs/2106.08634 (2021) - [i9]Sindre Benjamin Remman, Anastasios M. Lekkas:
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations. CoRR abs/2110.03292 (2021) - [i8]Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas:
Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning. CoRR abs/2111.02936 (2021) - 2020
- [j5]Glenn Bitar, Andreas B. Martinsen, Anastasios M. Lekkas, Morten Breivik:
Two-Stage Optimized Trajectory Planning for ASVs Under Polygonal Obstacle Constraints: Theory and Experiments. IEEE Access 8: 199953-199969 (2020) - [j4]Andreas B. Martinsen, Glenn Bitar, Anastasios M. Lekkas, Sébastien Gros:
Optimization-Based Automatic Docking and Berthing of ASVs Using Exteroceptive Sensors: Theory and Experiments. IEEE Access 8: 204974-204986 (2020) - [j3]Bjørn-Olav H. Eriksen, Glenn Bitar, Morten Breivik, Anastasios M. Lekkas:
Hybrid Collision Avoidance for ASVs Compliant With COLREGs Rules 8 and 13-17. Frontiers Robotics AI 7: 11 (2020) - [j2]Andreas B. Martinsen, Anastasios M. Lekkas, Sébastien Gros, Jon Arne Glomsrud, Tom Arne Pedersen:
Reinforcement Learning-Based Tracking Control of USVs in Varying Operational Conditions. Frontiers Robotics AI 7: 32 (2020) - [c4]Emil H. Thyri, Erlend A. Basso, Morten Breivik, Kristin Ytterstad Pettersen, Roger Skjetne, Anastasios M. Lekkas:
Reactive collision avoidance for ASVs based on control barrier functions. CCTA 2020: 380-387 - [i7]Andreas B. Martinsen, Anastasios M. Lekkas, Sebastien Gros:
Combining system identification with reinforcement learning-based MPC. CoRR abs/2004.03265 (2020) - [i6]Glenn Bitar, Andreas B. Martinsen, Anastasios M. Lekkas, Morten Breivik:
Trajectory Planning and Control for Automatic Docking of ASVs with Full-Scale Experiments. CoRR abs/2004.07793 (2020) - [i5]Andreas B. Martinsen, Anastasios M. Lekkas, Sebastien Gros:
Optimal model-based trajectory planning with static polygonal constraints. CoRR abs/2010.14428 (2020)
2010 – 2019
- 2019
- [c3]Glenn Bitar, Bjørn-Olav H. Eriksen, Anastasios M. Lekkas, Morten Breivik:
Energy-Optimized Hybrid Collision Avoidance for ASVs. ECC 2019: 2522-2529 - [i4]Bjørn-Olav H. Eriksen, Glenn Bitar, Morten Breivik, Anastasios M. Lekkas:
Hybrid Collision Avoidance for ASVs Compliant with COLREGs Rules 8 and 13-17. CoRR abs/1907.00198 (2019) - [i3]Glenn Bitar, Vegard N. Vestad, Anastasios M. Lekkas, Morten Breivik:
Warm-Started Optimized Trajectory Planning for ASVs. CoRR abs/1907.02696 (2019) - [i2]Glenn Bitar, Anastasios M. Lekkas, Morten Breivik:
Improvements to Warm-Started Optimized Trajectory Planning for ASVs. CoRR abs/1908.07311 (2019) - [i1]Andreas B. Martinsen, Anastasios M. Lekkas, Sebastien Gros:
Autonomous docking using direct optimal control. CoRR abs/1910.11625 (2019) - 2014
- [j1]Anastasios M. Lekkas, Thor I. Fossen:
Integral LOS Path Following for Curved Paths Based on a Monotone Cubic Hermite Spline Parametrization. IEEE Trans. Control. Syst. Technol. 22(6): 2287-2301 (2014) - [c2]Anastasios M. Lekkas, Thor I. Fossen:
Trajectory tracking and ocean current estimation for marine underactuated vehicles. CCA 2014: 905-910 - [c1]Anastasios M. Lekkas, Thor I. Fossen:
Minimization of cross-track and along-track errors for path tracking of marine underactuated vehicles. ECC 2014: 3004-3010
Coauthor Index
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