6 papers
Memory-State Critic for Asymmetric Actor-Critic with Application to Vision-Based Pursuit-Evasion
Arthur Louette, Alejandro Sánchez Roncero, Gaspard Lambrechts +4
In partially observable Markov decision processes, the optimal policy generally depends on the history of observations and past actions. Asymmetric actor-critic methods have become…
Battery-Aware Reinforcement Learning for Aggressive Quadrotor Flight
Alejandro Sanchez Roncero, Olov Andersson, Petter Ogren
Agile flight tasks such as drone racing and pursuit-evasion require strong acceleration and precise turns, but the available thrust changes as the battery discharges and voltage dr…
Marinarium: A Modular Experimental Facility for Reproducible Maritime and Space-Analog Field Robotics
Ignacio Torroba, David Dorner, Victor Nan Fernandez-Ayala +14
Field robotics research in maritime and space domains is constrained by a persistent gap between low-cost, low-fidelity simulation and costly offshore experimentation. Instrumented…
Learning Ordinal Response Policies in Rank-Based Stochastic Prize-Collecting Games
Malintha Fernando, Petter Ögren, Silun Zhang
The Team Orienteering Problem (TOP) generalizes many real-world multi-agent scheduling and routing tasks that occur in autonomous mobility, aerial logistics, and surveillance appli…
An Extended Convergence Result for Behaviour Tree Controllers
Christopher Iliffe Sprague, Petter Ögren
Behavior trees (BTs) are an optimally modular framework to assemble hierarchical hybrid control policies from a set of low-level control policies using a tree structure. Many robot…
On the similarities between Control Barrier Functions (CBFs) and Behavior Control Lyapunov Functions (BCLFs)
Petter Ögren
Control Barrier Functions (CBFs) is an important tool used to address situations with multiple concurrent control objectives, such as safety and goal convergence. In this paper we…