62 citations · 149 across the 19 of their papers we have counts for
6 papers · 1 filter
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion
Firas Al-Hafez, Guoping Zhao, Jan Peters +1
Imitation Learning (IL) holds great promise for enabling agile locomotion in embodied agents. However, many existing locomotion benchmarks primarily focus on simplified toy tasks,…
Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot
Luca Lach, Robert Haschke, Davide Tateo +4
The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation ta…
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
Firas Al-Hafez, Guoping Zhao, Jan Peters +1
Stateful policies play an important role in reinforcement learning, such as handling partially observable environments, enhancing robustness, or imposing an inductive bias directly…
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
Firas Al-Hafez, Davide Tateo, Oleg Arenz +2
Recent methods for imitation learning directly learn a -function using an implicit reward formulation rather than an explicit reward function. However, these methods generally r…
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks
Piotr Kicki, Puze Liu, Davide Tateo +4
Motion planning is a mature area of research in robotics with many well-established methods based on optimization or sampling the state space, suitable for solving kinematic motion…
Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators
Filip Bjelonic, Joonho Lee, Philip Arm +4
Parallel-elastic joints can improve the efficiency and strength of robots by assisting the actuators with additional torques. For these benefits to be realized, a spring needs to b…