no code implementations • 8 Jan 2024 • Chengjie Huang, Vahdat Abdelzad, Sean Sedwards, Krzysztof Czarnecki
We consider the problem of cross-sensor domain adaptation in the context of LiDAR-based 3D object detection and propose Stationary Object Aggregation Pseudo-labelling (SOAP) to generate high quality pseudo-labels for stationary objects.
no code implementations • 1 Jun 2022 • Scott Larter, Rodrigo Queiroz, Sean Sedwards, Atrisha Sarkar, Krzysztof Czarnecki
Modelling pedestrian behavior is crucial in the development and testing of autonomous vehicles.
no code implementations • 20 Jan 2022 • Jaeyoung Lee, Sean Sedwards, Krzysztof Czarnecki
In this work, after describing and motivating our problem with a simple example, we present a suitable constrained reinforcement learning algorithm that prevents learning instability, using recursive constraints.
no code implementations • 21 Aug 2019 • Marko Ilievski, Sean Sedwards, Ashish Gaurav, Aravind Balakrishnan, Atrisha Sarkar, Jaeyoung Lee, Frédéric Bouchard, Ryan De Iaco, Krzysztof Czarnecki
We explore the complex design space of behaviour planning for autonomous driving.
no code implementations • 11 Feb 2019 • Jaeyoung Lee, Aravind Balakrishnan, Ashish Gaurav, Krzysztof Czarnecki, Sean Sedwards
Machine learning can provide efficient solutions to the complex problems encountered in autonomous driving, but ensuring their safety remains a challenge.
1 code implementation • 11 Dec 2018 • Gidon Ernst, Sean Sedwards, Zhenya Zhang, Ichiro Hasuo
We present an algorithm that quickly finds falsifying inputs for hybrid systems, i. e., inputs that steer the system towards violation of a given temporal logic requirement.
Systems and Control
no code implementations • 14 Oct 2013 • Axel Legay, Sean Sedwards, Louis-Marie Traonouez
Markov decision processes (MDP) are useful to model concurrent process optimisation problems, but verifying them with numerical methods is often intractable.