1 citations · 1 across the 6 of their papers we have counts for
6 papers
Accelerating Reinforcement Learning via MPC Solver-Gradient Guidance for Weights-varying MPC
Baha Zarrouki, Arslan Thobani, Jasper Hoffmann +6
In Model Predictive Control (MPC), cost-function weights shape closed-loop behavior, yet changing conditions often make fixed parametrizations suboptimal and motivate context-depen…
Trajectory Planning and Control near the Limits: an Open Experimental Benchmark on the RoboRacer Platform
Mattia Piccinini, Patrick Zambiasi, Aniello Mungiello +3
We present a modular framework to benchmark new and existing methods for trajectory planning and control in high-acceleration maneuvers that push autonomous driving to the limits.…
Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets?
Dingrui Wang, Zhihao Liang, Hongyuan Ye +13
While recent video world models can generate highly realistic videos, their ability to perform semantic reasoning and planning remains unclear and unquantified. We introduce Target…
MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation
Felix Jahncke, Johannes Betz
Developing robust, efficient navigation algorithms is challenging. Rule-based methods offer interpretability and modularity but struggle with learning from large datasets, while en…
Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms: Challenges and a Roadmap
Jianye Xu, Johannes Betz, Armin Mokhtarian +11
This article proposes a roadmap to address the current challenges in small-scale testbeds for Connected and Automated Vehicles (CAVs) and robot swarms. The roadmap is a joint effor…
AV4EV: Open-Source Modular Autonomous Electric Vehicle Platform for Making Mobility Research Accessible
Zhijie Qiao, Mingyan Zhou, Zhijun Zhuang +10
When academic researchers develop and validate autonomous driving algorithms, there is a challenge in balancing high-performance capabilities with the cost and complexity of the ve…