Concept
Robot navigation
Publications associées (357)
VDM-based navigation for Delta-wing UAVs: Models, calibration, implementation
Autonomous navigation of small UAVs is typically based on the integration of inertial navigation systems (INS) together with global navigation satellite systems (GNSS). However, GNSS signals can face various forms of interference affecting their continuous ...
EPFL2024Sense in Motion with Belief Clustering: Efficient Gas Source Localization with Mobile Robots
Alcherio Martinoli, Wanting Jin
Given the patchy nature of gas plumes and the slow response of conventional gas sensors, the use of mobile robots for Gas Source Localization (GSL) tasks presents significant challenges. These aspects increase the difficulties in obtaining gas measurement ...
2024VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones
Jan Skaloud, Gabriel François Laupré
Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...
2024Soft Robot Shape Estimation With IMUs Leveraging PCC Kinematics for Drift Filtering
Josephine Anna Eleanor Hughes, Francesco Stella
The control possibilities for soft robots have long been hindered by the need for reliable methods to estimate their configuration. Inertial measurement units (IMUs) can solve this challenge, but they are affected by well-known drift issues. This letter pr ...
Piscataway2024Inverse Reinforcement Learning of Pedestrian-Robot Coordination
Aude Billard, David Julian Gonon
We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals
Aude Billard, José del Rocio Millán Ruiz, Fumiaki Iwane
During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...
Berlin2023