6 papers
ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworks
Bojan DerajiÄ, 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 DerajiÄ, 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…
Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environments
Bojan DerajiÄ, 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…
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)…