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Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Jang S, Jeong H, Yang H. MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation. Robotics. 2023; 12(4):119. https://doi.org/10.3390/robotics12040119

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The other kind of wave is a polarized wave. Polarized waves are light waves in which the vibrations occur in a single plane. Plane polarized light consists of waves in which the direction of vibration is the same for all waves. In the image above, you can see that a plane polarized light vibrates on only one plane. The process of transforming unpolarized light into polarized light is known as polarization. The devices like the polarizers you see are used for the polarization of light.

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Transverse waves are waves, in which the movement of the particles in the wave is perpendicular to the direction of motion of the wave.

Jang, S.; Jeong, H.; Yang, H. MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation. Robotics 2023, 12, 119. https://doi.org/10.3390/robotics12040119

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Abstract: We present a novel framework, multi-view unified reinforcement learning for robotic manipulation (MURM), which efficiently utilizes multiple camera views to train a goal-conditioned policy for a robot to perform complex tasks. The MURM framework consists of three main phases: (i) demo collection from an expert, (ii) representation learning, and (iii) offline reinforcement learning. In the demo collection phase, we design a scripted expert policy that uses privileged information, such as Cartesian coordinates of a target and goal, to solve the tasks. We add noise to the expert policy to provide sufficient interactive information about the environment, as well as suboptimal behavioral trajectories. We designed three tasks in a Pybullet simulation environment, including placing an object in a desired goal position and picking up various objects that are randomly positioned in the environment. In the representation learning phase, we use a vector-quantized variational autoencoder (VQVAE) to learn a more structured latent representation that makes it feasible to train for RL compared to high-dimensional raw images. We train VQVAE models for each distinct camera view and define the best viewpoint settings for training. In the offline reinforcement learning phase, we use the Implicit Q-learning (IQL) algorithm as our baseline and introduce a separated Q-functions method and dropout method that can be implemented in multi-view settings to train the goal-conditioned policy with supervised goal images. We conduct experiments in simulation and show that the single-view baseline fails to solve complex tasks, whereas MURM is successful. Keywords: goal-conditioned reinforcement learning (GCRL); multiple camera views; robot manipulation; vector-quantized variational autoencoders (VQVAE)

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Jang, Seongwon, Hyemi Jeong, and Hyunseok Yang. 2023. "MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation" Robotics 12, no. 4: 119. https://doi.org/10.3390/robotics12040119

The electric field of light follows an elliptical propagation. The amplitude and phase difference between the two linear components are not equal.

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There are two linear components in the electric field of light that are perpendicular to each other such that their amplitudes are equal, but the phase difference is π/2. The propagation of the occurring electric field will be in a circular motion.

Jang, Seongwon, Hyemi Jeong, and Hyunseok Yang. 2023. "MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation" Robotics 12, no. 4: 119. https://doi.org/10.3390/robotics12040119

Jang, S.; Jeong, H.; Yang, H. MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation. Robotics 2023, 12, 119. https://doi.org/10.3390/robotics12040119

Light is the interaction of electric and magnetic fields travelling through space. The electric and magnetic vibrations of a light wave occur perpendicularly to each other. The electric field moves in one direction and the magnetic field in another ‘perpendicular to each other. So, we have one plane occupied by an electric field, another plane of the magnetic field perpendicular to it, and the direction of travel is perpendicular to both. These electric and magnetic vibrations can occur in numerous planes. A light wave that is vibrating in more than one plane is known as unpolarized light. The light emitted by the sun, by a lamp or a tube light are all unpolarised light sources. As you can see in the image below, the direction of propagation is constant, but the planes on which the amplitude occurs are changing.

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Polarization, in Physics, is defined as a phenomenon caused due to the wave nature of electromagnetic radiation. Sunlight travels through the vacuum to reach the Earth, which is an example of an electromagnetic wave. These waves are called electromagnetic waves because they form when an electric field interacts with a magnetic field. In this article, you will learn about two types of waves, transverse waves and longitudinal waves. You will also learn about polarization and plane polarised light.

Jang S, Jeong H, Yang H. MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation. Robotics. 2023; 12(4):119. https://doi.org/10.3390/robotics12040119

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