34 citations · 50 across the 32 of their papers we have counts for
35 papers
Pretrained Features as Teachers, Not States: Compact Latent World Models for Visual Planning
Yanbo Wang, Nan Lin, Wendelin Böhmer +1
A key design choice in visual world models is what information the latent state is encouraged to preserve. Models that learn a latent space with only a latent-prediction objective…
Risk-Aware Belief Control Barrier Functions over Random Finite Sets
Shaohang Han, Gang Chen, Yixi Cai +5
Ensuring robot safety in unknown, dynamic environments is a fundamental requirement. It involves inferring the states of an unknown and time-varying number of moving objects from n…
Language-Driven Cost Optimization for Autonomous Driving
Diego Martinez-Baselga, Khaled Mustafa, Javier Alonso-Mora
The driving behavior of autonomous vehicles is typically governed by the cost function of their motion planner, which encodes objectives such as speed tracking, smoothness, lane ke…
STEM: Semantic Target Search and Exploration using MAVs in Cluttered Environments
Nikhil Sethi, Max Lodel, Laura Ferranti +2
Autonomous target search is crucial for deploying Micro Aerial Vehicles (MAVs) in emergency response and rescue missions. Existing approaches either focus on 2D semantic navigation…
Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations
Lasse Peters, Laura Ferranti, Andrea Bajcsy +1
Imitation learning powered by generative models has proven effective for modeling complex single-agent behaviors. However, teaching multi-agent systems, like multiple arms or vehic…
OpenSGA: Efficient 3D Scene Graph Alignment in the Open World
Gang Chen, Sebastián Barbas Laina, Stefan Leutenegger +1
Scene graph alignment establishes object correspondences between two 3D scene graphs constructed from partially overlapping observations. This enables efficient scene understanding…
Learning Semantic Priorities for Autonomous Target Search
Max Lodel, Nils Wilde, Robert Babuška +1
The use of semantic features can improve the efficiency of target search in unknown environments for robotic search and rescue missions. Current target search methods rely on train…
Building Explicit World Model for Zero-Shot Open-World Object Manipulation
Xiaotong Li, Gang Chen, Javier Alonso-Mora
Open-world object manipulation remains a fundamental challenge in robotics. While Vision-Language-Action (VLA) models have demonstrated promising results, they rely heavily on larg…
BEACON: Language-Conditioned Navigation Affordance Prediction under Occlusion
Xinyu Gao, Gang Chen, Javier Alonso-Mora
Language-conditioned local navigation requires a robot to infer a nearby traversable target location from its current observation and an open-vocabulary, relational instruction. Ex…
Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing
Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2
Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…
MobileOcc: A Human-Aware Semantic Occupancy Dataset for Mobile Robots
Junseo Kim, Guido Dumont, Xinyu Gao +3
Dense 3D semantic occupancy perception is critical for mobile robots operating in pedestrian-rich environments, yet it remains underexplored compared to its application in autonomo…
From Data to Safe Mobile Robot Navigation: An Efficient and Modular Robust MPC Design Pipeline
Dennis Benders, Johannes Köhler, Robert Babuška +2
Model predictive control (MPC) is a powerful strategy for planning and control in autonomous mobile robot navigation. However, ensuring safety in real-world deployments remains cha…
A Vehicle System for Navigating Among Vulnerable Road Users Including Remote Operation
Oscar de Groot, Alberto Bertipaglia, Hidde Boekema +21
We present a vehicle system capable of navigating safely and efficiently around Vulnerable Road Users (VRUs), such as pedestrians and cyclists. The system comprises key modules for…
TamedPUMA: safe and stable imitation learning with geometric fabrics
Saray Bakker, Rodrigo Pérez-Dattari, Cosimo Della Santina +2
Using the language of dynamical systems, Imitation learning (IL) provides an intuitive and effective way of teaching stable task-space motions to robots with goal convergence. Yet,…
Pushing Through Clutter With Movability Awareness of Blocking Obstacles
Joris J. Weeda, Saray Bakker, Gang Chen +1
Navigation Among Movable Obstacles (NAMO) poses a challenge for traditional path-planning methods when obstacles block the path, requiring push actions to reach the goal. We propos…
Particle-based Instance-aware Semantic Occupancy Mapping in Dynamic Environments
Gang Chen, Zhaoying Wang, Wei Dong +1
Representing the 3D environment with instance-aware semantic and geometric information is crucial for interaction-aware robots in dynamic environments. Nevertheless, creating such…
Embedded Hierarchical MPC for Autonomous Navigation
Dennis Benders, Johannes Köhler, Thijs Niesten +3
To efficiently deploy robotic systems in society, mobile robots must move autonomously and safely through complex environments. Nonlinear model predictive control (MPC) methods pro…
Decentralized Multi-Agent Trajectory Planning in Dynamic Environments with Spatiotemporal Occupancy Grid Maps
Siyuan Wu, Gang Chen, Moji Shi +1
This paper proposes a decentralized trajectory planning framework for the collision avoidance problem of multiple micro aerial vehicles (MAVs) in environments with static and dynam…
Evaluating Dynamic Environment Difficulty for Obstacle Avoidance Benchmarking
Moji Shi, Gang Chen, Álvaro Serra Gómez +2
Dynamic obstacle avoidance is a popular research topic for autonomous systems, such as micro aerial vehicles and service robots. Accurately evaluating the performance of dynamic ob…
SHINE: Social Homology Identification for Navigation in Crowded Environments
Diego Martinez-Baselga, Oscar de Groot, Luzia Knoedler +3
Navigating mobile robots in social environments remains a challenging task due to the intricacies of human-robot interactions. Most of the motion planners designed for crowded and…
Auto-Encoding Bayesian Inverse Games
Xinjie Liu, Lasse Peters, Javier Alonso-Mora +2
When multiple agents interact in a common environment, each agent's actions impact others' future decisions, and noncooperative dynamic games naturally capture this coupling. In in…
Topology-Driven Parallel Trajectory Optimization in Dynamic Environments
Oscar de Groot, Laura Ferranti, Dariu M. Gavrila +1
Ground robots navigating in complex, dynamic environments must compute collision-free trajectories to avoid obstacles safely and efficiently. Nonconvex optimization is a popular me…
Interaction-Aware Sampling-Based MPC with Learned Local Goal Predictions
Walter Jansma, Elia Trevisan, Álvaro Serra-Gómez +1
Motion planning for autonomous robots in tight, interaction-rich, and mixed human-robot environments is challenging. State-of-the-art methods typically separate prediction and plan…
Rule-Based Lloyd Algorithm for Multi-Robot Motion Planning and Control with Safety and Convergence Guarantees
Manuel Boldrer, Alvaro Serra-Gomez, Lorenzo Lyons +3
This paper presents a distributed rule-based Lloyd algorithm (RBL) for multi-robot motion planning and control. The main limitations of the basic Loyd-based algorithm (LB) concern…