21 citations · 26 across the 11 of their papers we have counts for
13 papers
Active Interaction-Aware Model Predictive Path Integral via Ego-Conditioned Generative Predictions
Khaled A. Mustafa, Mohamed-Khalil Bouzidi, Christian Schlauch +4
Dense traffic is inherently interactive. The ego vehicle and surrounding agents continuously influence each other's reactions, making "what-if" reasoning essential for safe and eff…
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections
Zhaoting Li, Gang Chen, Javier Alonso-Mora +2
Diffusion policies have recently emerged as a powerful framework for robotic manipulation. However, like other behavior cloning methods, they remain vulnerable to distributional sh…
Studying the Effect of Explicit Interaction Representations on Learning Scene-level Distributions of Human Trajectories
Anna Mészáros, Javier Alonso-Mora, Jens Kober
Effectively capturing the joint distribution of all agents in a scene is relevant for predicting the true evolution of the scene and in turn providing more accurate information to…
Active Disturbance Rejection Control for Trajectory Tracking of a Seagoing USV: Design, Simulation, and Field Experiments
Jelmer van der Saag, Elia Trevisan, Wouter Falkena +1
Unmanned Surface Vessels (USVs) face significant control challenges due to uncertain environmental disturbances like waves and currents. This paper proposes a trajectory tracking c…
Dynamic Risk-Aware MPPI for Mobile Robots in Crowds via Efficient Monte Carlo Approximations
Elia Trevisan, Khaled A. Mustafa, Godert Notten +2
Deploying mobile robots safely among humans requires the motion planner to account for the uncertainty in the other agents' predicted trajectories. This remains challenging in trad…
Predictability Awareness for Efficient and Robust Multi-Agent Coordination
Roman Chiva Gil, Daniel Jarne Ornia, Khaled A. Mustafa +1
To safely and efficiently solve motion planning problems in multi-agent settings, most approaches attempt to solve a joint optimization that explicitly accounts for the responses t…
RACP: Risk-Aware Contingency Planning with Multi-Modal Predictions
Khaled A. Mustafa, Daniel Jarne Ornia, Jens Kober +1
For an autonomous vehicle to operate reliably within real-world traffic scenarios, it is imperative to assess the repercussions of its prospective actions by anticipating the uncer…
ROME: Robust Multi-Modal Density Estimator
Anna Mészáros, Julian F. Schumann, Javier Alonso-Mora +2
The estimation of probability density functions is a fundamental problem in science and engineering. However, common methods such as kernel density estimation (KDE) have been demon…
Predictable Reinforcement Learning Dynamics through Entropy Rate Minimization
Daniel Jarne Ornia, Giannis Delimpaltadakis, Jens Kober +1
In Reinforcement Learning (RL), agents have no incentive to exhibit predictable behaviors, and are often pushed (through e.g. policy entropy regularisation) to randomise their acti…
TrajFlow: Learning Distributions over Trajectories for Human Behavior Prediction
Anna Mészáros, Julian F. Schumann, Javier Alonso-Mora +2
Predicting the future behavior of human road users is an important aspect for the development of risk-aware autonomous vehicles. While many models have been developed towards this…
Probabilistic Risk Assessment for Chance-Constrained Collision Avoidance in Uncertain Dynamic Environments
Khaled A. Mustafa, Oscar de Groot, Xinwei Wang +2
Balancing safety and efficiency when planning in crowded scenarios with uncertain dynamics is challenging where it is imperative to accomplish the robot's mission without incurring…
Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving
Xinwei Wang, Zirui Li, Javier Alonso-Mora +1
Risk assessment is a crucial component of collision warning and avoidance systems in intelligent vehicles. To accurately detect potential vehicle collisions, reachability-based for…
Prediction-Based Reachability Analysis for Collision Risk Assessment on Highways
Xinwei Wang, Zirui Li, Javier Alonso-Mora +1
Real-time safety systems are crucial components of intelligent vehicles. This paper introduces a prediction-based collision risk assessment approach on highways. Given a point mass…