Humanoid Shape Research Articles

Educational Soft Underwater Robot with an Electromagnetic Actuation.

As demonstrated by the Soft Robotics Toolkit Platform, compliant robotics pose an exciting educational opportunity. Underwater robotics using soft undulating fins is an expansive research topic with applications such as exploration of underwater life or replicating 3d swarm behavior. To make this research area accessible for education we developed Educational Soft Underwater Robot with Electromagnetic Actuation (ESURMA), a humanoid soft underwater robot. We achieved advances in simplicity, modularity, and performance by implementing electromagnetic actuation into the caudal fin. An electromagnet, including electronics, is placed in a waterproof housing, and permanent magnets are embedded in a soft silicone cast tail. The force from their magnetic interaction results in a bending movement of the tail. The magnetic actuation is simple to implement and requires no mechanical connection between the actuated component and the electrically controlled coil. This enables robust waterproofing and makes the device fully modular. Thanks to the direct and immediate transmission of force, experimental flapping frequencies of 14 Hz were achieved, an order of magnitude higher compared to pneumatically actuated tails. The completely silent actuation of the caudal fin enables a maximum swimming speed of 14.3 cm/s. With its humanoid shape, modular composition, and cost efficiency ESURMA represents an attractive platform for education and demonstrates an alternative method of actuating soft structures.

Pareto Optimized Large Mask Approach for Efficient and Background Humanoid Shape Removal

We introduce deep learning-based methodology for removing unwanted human-like shapes in videos. The method uses Pareto-optimized Generative Adversarial Networks (GANs) technology, which is a novel contribution. The system automatically selects the Region of Interest (ROI) for each humanoid shape and uses a skeleton detection module to determine which humanoid shape to retain. The semantic masks of human like shapes are created using a semantic-aware occlusion-robust model that has four primary components: feature extraction, and local, global, and semantic branches. The global branch encodes occlusion-aware information to make the extracted features resistant to occlusion, while the local branch retrieves fine-grained local characteristics. A modified big mask inpainting approach is employed to eliminate a person from the image, leveraging Fast Fourier convolutions and utilizing polygonal chains and rectangles with unpredictable aspect ratios. The inpainter network takes the input image and the mask to create an output image excluding the background humanoid shapes. The generator uses an encoder-decoder structure with included skip connections to recover spatial information and dilated convolution and squeeze and excitation blocks to make the regions behind the humanoid shapes consistent with their surroundings. The discriminator avoids dissimilar structure at the patch scale, and the refiner network catches features around the boundaries of each background humanoid shape. The method is evaluated on two video object segmentation datasets (DAVIS and YouTube-VOS) and a database of 66 distinct video sequences of people behind a desk in an office environment. The efficiency was assessed using the Structural Similarity Index Measure (SSIM), Frechet Inception Distance (FID), and Learned Perceptual Image Patch Similarity (LPIPS) metrics and showed promising results in fully automated background person removal task.

Virtual body anthropomorphism increases drift in self‐location: Further support for the humanoid shape rule

AbstractPrevious studies on bodily self‐consciousness (BCS) have shown that self‐location and body ownership are prone to changes based on the perceptual appearances of the fake virtual body. In the current study with 36 participants, we assessed the influence of virtual avatar anthropomorphism and the synchronicity of the visuo‐tactile stimulation on self‐location using a virtual reality full‐body illusion experiment. During the experiment, half of the participants observed a gender‐matched full‐body humanoid avatar from a first‐person perspective (1PP) and the other half observed a less anthropomorphic full‐body cubical avatar from 1PP while they were receiving synchronous and asynchronous visuo‐tactile stimulation. Results showed a significant main effect of the synchronicity of the visuo‐tactile stimulation and avatar body type on self‐location but no significant interaction was found between them. Moreover, the results of the self‐report questionnaire provide additional evidence showing that participants who received synchronous visuo‐tactile stimulation, experienced not only greater changes in the feeling of self‐location, but also, increased ownership, and referral of touch. Our results provided further support for the previous findings that showed evidence for the effect of virtual avatar appearance on BCS.

Kinematics Analysis of Serial-Parallel Hybrid Humanoid Robot in Reaching Movement

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/07.jpg"" width=""300"" />Serial-parallel hybrid robot</div> As the demand to the practical operation ability of humanoid robots improving, serial-parallel hybrid structure has started to be used in the research of humanoid robot. However, analytical solutions of the forward and inverse kinematics are hard to obtain due to the redundancy of humanoid robot and the complex topology of hybrid structure. Besides, humanoid robots should have the capability to complete complicated operation in the low structured task workspace. So, it should have not only the humanoid shape but also the behavior that adapts to the direct interaction with people. In this work, a novel 4-DOF hybrid humanoid robot was taken as an example, the forward kinematics equation was derived, the theory of screws and lie group and lie algebra were applied to calculate the end velocity. A numerical calculation method based on neurophysiology sensorimotor transformation model and fuzzy logic compensator was proposed to solve the inverse kinematics in reaching movement. The proposed strategy can make the robot execute reaching movements with human-like posture. Simulation and test results validate the effectiveness respectively. </span>

Radiation phantom with humanoid shape and adjustable thickness (RPHAT)

A new radiation phantom with humanoid shape and adjustable thickness (RPHAT) has been developed. Unlike the RANDO® phantom which is a fixed thickness, this newly designed phantom has adjustable thickness to address the range of thicknesses of real-world patients. RPHAT allows adjustment of the body thickness by being sliced in the coronal (instead of axial) direction. Centre slices are designed so that more sections can be added or removed while maintaining the anthropomorphic shape. A prototype of the new phantom has been successfully used in a study investigating peripheral dose delivery, where the amount of scatter within the patient, and therefore the patient thickness, plays a critical role in dose deposition. This newly designed phantom is an important tool to improve the quality of radiation therapy.

Dynamically-Stable Motion Planning for Humanoid Robots

We present an approach to path planning for humanoid robots that computes dynamically-stable, collision-free trajectories from full-body posture goals. Given a geometric model of the environment and a statically-stable desired posture, we search the configuration space of the robot for a collision-free path that simultaneously satisfies dynamic balance constraints. We adapt existing randomized path planning techniques by imposing balance constraints on incremental search motions in order to maintain the overall dynamic stability of the final path. A dynamics filtering function that constrains the ZMP (zero moment point) trajectory is used as a post-processing step to transform statically-stable, collision-free paths into dynamically-stable, collision-free trajectories for the entire body. Although we have focused our experiments on biped robots with a humanoid shape, the method generally applies to any robot subject to balance constraints (legged or not). The algorithm is presented along with computed examples using both simulated and real humanoid robots.