… not equally accurate in all the robot work space, rendering the … power of deep learning and
conditional generative models to … approach on a robot table tennis setup in simulation and in …

… rendered from virtual 3D scenes, and robots can be trained to navigate in and … in simulated
ones. One of the most promising ways to achieve this is by learning and applying generative …

… Methods for utilizing unlabeled data can have a huge potential to further accelerate robotic
learning. We … The simulated and real robot setups we used are displayed at the bottom. …

… This requires flexible generative planning that can combine … simulation is required, so we
attempt to learn on a real robot … which might not be true for a robot learning online in the wild. …

… in simulation, P-GAIL is applied to a dual-arm humanoid robot tasked with flipping a handkerchief
and successfully learns … learning ability and sample efficiency of PGAIL in robotic cloth …

… As a proof of concept, we recorded in simulation some examples of the humanoid robot moving
its arm … Calinon, “Robot learning with task-parameterized generative models,” in Springer …

… sample-efficient robot learning, we apply the algorithm to learn robot locomotion, manipulation,
and navigation tasks from scratch in the real world on 4 robots, without simulators. The …

… learning and reinforcement learning has been increasingly used in robot learning field, which
allows robots … the demonstration trajectories in the simulation environment, and record the …

… simulation (a), and deploy it on a physical robot (… learning with generative models for
trajectories to explicitly train a policy to adapt to a wide range of randomized dynamics in simulation, …

… robot, the expert will fit probability distributions for these quantities. Finally, the validated
simulation model … in buffer sizes, robot capabilities, job scheduling, and so on. Although modern …