91 citations · 222 across the 23 of their papers we have counts for
25 papers
GAMBIT: Learning to Plan Continuous Multi-Robot Trajectories
Rishabh Jain, Akmaral Moldagalieva, Lorenzo Magnino +5
GAMBIT is an opening chess move in which a player sacrifices a piece, typically a pawn, to gain a positional advantage later in the game. Analogously, in multi-robot coordination,…
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…
Lifelong Multi-Subsystem Pickup and Delivery with Buffer-Limited Handover Stations
Chuanlong Zang, Isabelle Barz, Anna Mannucci +3
Coordinating payload transfers between subsystems is a critical challenge in lifelong Multi-Agent Pickup and Delivery (MAPD). We study systems where agents are confined to separate…
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…
CrazyMARL: Decentralized Direct Motor Control Policies for Cooperative Aerial Transport of Cable-Suspended Payloads
Viktor Lorentz, Khaled Wahba, Sayantan Auddy +2
Collaborative transportation of cable-suspended payloads by teams of UAVs has the potential to enhance payload capacity, adapt to different payload shapes, and provide built-in com…
iDb-RRT: Sampling-based Kinodynamic Motion Planning with Motion Primitives and Trajectory Optimization
Joaquim Ortiz-Haro, Wolfgang Hönig, Valentin N. Hartmann +2
Rapidly-exploring Random Trees (RRT) and its variations have emerged as a robust and efficient tool for finding collision-free paths in robotic systems. However, adding dynamic con…
iDb-A*: Iterative Search and Optimization for Optimal Kinodynamic Motion Planning
Joaquim Ortiz-Haro, Wolfgang Hoenig, Valentin N. Hartmann +1
Motion planning for robotic systems with complex dynamics is a challenging problem. While recent sampling-based algorithms achieve asymptotic optimality by propagating random contr…
Survey of Simulators for Aerial Robots: An Overview and In-Depth Systematic Comparisons
Cora A. Dimmig, Giuseppe Silano, Kimberly McGuire +4
Uncrewed Aerial Vehicle (UAV) research faces challenges with safety, scalability, costs, and ecological impact when conducting hardware testing. High-fidelity simulators offer a vi…
Kinodynamic Motion Planning for a Team of Multirotors Transporting a Cable-Suspended Payload in Cluttered Environments
Khaled Wahba, Joaquim Ortiz-Haro, Marc Toussaint +1
We propose a motion planner for cable-driven payload transportation using multiple unmanned aerial vehicles (UAVs) in an environment cluttered with obstacles. Our planner is kinody…
MRNAV: Multi-Robot Aware Planning and Control Stack for Collision and Deadlock-free Navigation in Cluttered Environments
Baskın Şenbaşlar, Pilar Luiz, Wolfgang Hönig +1
Multi-robot collision-free and deadlock-free navigation in cluttered environments with static and dynamic obstacles is a fundamental problem for many applications. We introduce MRN…
Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches
Pia Hanfeld, Khaled Wahba, Marina M. -C. Höhne +2
Autonomous flying robots, such as multirotors, often rely on deep learning models that make predictions based on a camera image, e.g. for pose estimation. These models can predict…
Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors
Pia Hanfeld, Marina M. -C. Höhne, Michael Bussmann +1
Autonomous flying robots, e.g. multirotors, often rely on a neural network that makes predictions based on a camera image. These deep learning (DL) models can compute surprising re…
Efficient Optimization-based Cable Force Allocation for Geometric Control of a Multirotor Team Transporting a Payload
Khaled Wahba, Wolfgang Hönig
We consider transporting a heavy payload that is attached to multiple multirotors. The current state-of-the-art controllers either do not avoid inter-robot collision at all, leadin…
RLSS: Real-time, Decentralized, Cooperative, Networkless Multi-Robot Trajectory Planning using Linear Spatial Separations
Baskın Şenbaşlar, Wolfgang Hönig, Nora Ayanian
Trajectory planning for multiple robots in shared environments is a challenging problem especially when there is limited communication available or no central entity. In this artic…
Virtual Omnidirectional Perception for Downwash Prediction within a Team of Nano Multirotors Flying in Close Proximity
Akmaral Moldagalieva, Wolfgang Hönig
Teams of flying robots can be used for inspection, delivery, and construction tasks, in which they might be required to fly very close to each other. In such close-proximity cases,…
Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation
Marc Toussaint, Jason Harris, Jung-Su Ha +2
Task and Motion Planning has made great progress in solving hard sequential manipulation problems. However, a gap between such planning formulations and control methods for reactiv…
Lighthouse Positioning System: Dataset, Accuracy, and Precision for UAV Research
Arnaud Taffanel, Barbara Rousselot, Jonas Danielsson +5
The Lighthouse system was originally developed as tracking system for virtual reality applications. Due to its affordable price, it has also found attractive use-cases in robotics…
RLSS: Real-time Multi-Robot Trajectory Replanning using Linear Spatial Separations
Baskın Şenbaşlar, Wolfgang Hönig, Nora Ayanian
Trajectory replanning is a critical problem for multi-robot teams navigating dynamic environments. We present RLSS (Replanning using Linear Spatial Separations): a real-time trajec…
Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions
Guanya Shi, Wolfgang Hönig, Yisong Yue +1
In this paper, we present Neural-Swarm, a nonlinear decentralized stable controller for close-proximity flight of multirotor swarms. Close-proximity control is challenging due to t…
Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors
Artem Molchanov, Tao Chen, Wolfgang Hönig +3
Quadrotor stabilizing controllers often require careful, model-specific tuning for safe operation. We use reinforcement learning to train policies in simulation that transfer remar…
Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery
Hang Ma, Wolfgang Hönig, T. K. Satish Kumar +2
The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token Passing (TP) i…
Overview: A Hierarchical Framework for Plan Generation and Execution in Multi-Robot Systems
Hang Ma, Wolfgang Hönig, Liron Cohen +5
The authors present an overview of a hierarchical framework for coordinating task- and motion-level operations in multirobot systems. Their framework is based on the idea of using…
Path Planning with Kinematic Constraints for Robot Groups
Wolfgang Hönig, T. K. Satish Kumar, Liron Cohen +3
Path planning for multiple robots is well studied in the AI and robotics communities. For a given discretized environment, robots need to find collision-free paths to a set of spec…
Downwash-Aware Trajectory Planning for Large Quadrotor Teams
James A. Preiss, Wolfgang Hönig, Nora Ayanian +1
We describe a method for formation-change trajectory planning for large quadrotor teams in obstacle-rich environments. Our method decomposes the planning problem into two stages: a…