4 citations · 5 across the 8 of their papers we have counts for
10 papers
Learning Reachability-Based Safety Representations for Real-Time Robot Navigation in Unknown and Dynamic Environments
Bojan Derajić
Safe robot navigation in unknown, dynamic environments requires more than geometric collision checking: a robot still far from an obstacle may be unable to avoid it because of its…
VertexCBF: Improving Neural Control Barrier Functions via Vertex-Restricted Control Search
Bojan Derajić, Sebastian Bernhard, Wolfgang Hönig
As the number of autonomous robots continues to grow, safety becomes increasingly important. Control barrier functions (CBFs) provide a theoretically grounded framework for ensurin…
CN-CBF: Composite Neural Control Barrier Function for Robot Navigation in Dynamic Environments
Bojan Derajić, Sebastian Bernhard, Wolfgang Hönig
Safe navigation of autonomous robots remains one of the core challenges in the field, especially in dynamic and uncertain environments. One prevalent approach is safety filtering b…
ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworks
Bojan Derajić, Sebastian Bernhard, Wolfgang Hönig
Control barrier functions (CBFs) have been demonstrated as an effective method for safety-critical control of autonomous systems. Although CBFs are simple to deploy, their design r…
Residual Neural Terminal Constraint for MPC-based Collision Avoidance in Dynamic Environments
Bojan Derajić, Mohamed-Khalil Bouzidi, Sebastian Bernhard +1
In this paper, we propose a hybrid MPC local planner that uses a learning-based approximation of a time-varying safe set, derived from local observations and applied as the MPC ter…
Model Predictive Control for Crowd Navigation via Learning-Based Trajectory Prediction
Mohamed Parvez Aslam, Bojan Derajic, Mohamed-Khalil Bouzidi +2
Safe navigation in pedestrian-rich environments remains a key challenge for autonomous robots. This work evaluates the integration of a deep learning-based Social-Implicit (SI) ped…
Generative AI for Autonomous Driving: A Review
Katharina Winter, Abhishek Vivekanandan, Rupert Polley +17
Generative AI (GenAI) is rapidly advancing the field of Autonomous Driving (AD), extending beyond traditional applications in text, image, and video generation. We explore how gene…
Reachability-Based Contingency Planning against Multi-Modal Predictions with Branch MPC
Mohamed-Khalil Bouzidi, Bojan Derajic, Daniel Goehring +1
This paper presents a novel contingency planning framework that integrates learning-based multi-modal predictions of traffic participants into Branch Model Predictive Control (MPC)…
Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environments
Bojan Derajić, Mohamed-Khalil Bouzidi, Sebastian Bernhard +1
This paper presents a novel learning-based approach for online estimation of maximal safe sets for local trajectory planning in unknown static environments. The neural representati…
Motion Planning under Uncertainty: Integrating Learning-Based Multi-Modal Predictors into Branch Model Predictive Control
Mohamed-Khalil Bouzidi, Bojan Derajic, Daniel Goehring +1
In complex traffic environments, autonomous vehicles face multi-modal uncertainty about other agents' future behavior. To address this, recent advancements in learningbased motion…