@proceedings{Gubbala2025_SII,

title = {Deformation Analysis and Prediction of Drop-Stitch Reinforced Inflatable Robot Link for 1DOF and 2DOF Motion},

author = {Gangadhara Naga Sai Gubbala, Masato Nagashima, Hiroki Mori, Young Ah Seong, Hiroki Sato, Ryuma Niiyama, Yuki Suga, Tetsuya Ogata},

year  = {2025},

date = {2025-01-22},

urldate = {2025-01-22},

abstract = {In this study, we observe the dynamic behavior of an inflatable robot arm with an internally reinforced drop-stitch structure. We examine the deformation during motion of 1 and 2 degrees of freedom (DOF) for an inflatable body. The inflatable robot arm has a soft inflatable body as links and rigid servo actuators as joints. We implemented a sinusoidal motion for inflatable links for various payload conditions and analyzed them using a Motion Capture system. To estimate the dynamic deformation of the balloon in motion, we have defined a Deformation Index (DI) metric. Angle, current of the actuator (servo), and DI are used as input to polynomial regression to predict the end effector position. With this analysis, we can understand the complexity of modeling the nonlinear behavior of inflatable links for multi-DOF motion. We observed DI helps improve the prediction of the end effector position by including deformation information. However, the results demonstrate the limitations of polynomial regression analysis of an internally reinforced inflatable robot arm link.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Sasaki2025_SII,

title = {Subterranean Locomotion of Half-Inch Diameter Soft Earthworm Robot with Bellows Segments},

author = {Genta Sasaki, Kazuya Kudo, Ryuma Niiyama},

year  = {2025},

date = {2025-01-22},

urldate = {2025-01-22},

abstract = {Moving through the ground with a soft robot is a difficult task. Soft locomotion can move without damaging the environment, such as tree roots, but even in just a few centimeters of soil, high friction and resistance forces occur. Differences in soil topography and moisture content also affect the motion. We therefore developed a small, bellows-shaped earthworm robot with an outer diameter of 12 mm. The robot consists of silicone rubber and shape memory alloy wire, and the inside of the bellows is filled with air. When electric current is applied to the shape memory alloy wire, the convex part of the bellows contracts and stretches in the axial direction, generating a force for movement. When no current is applied, it is used as an anchoring segment. We have experimented with 16 different patterns of soil topography and moisture content, and succeeded in realizing soft-robotic subterranean locomotion.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Hirade2025_SII,

title = {Curriculum Reinforcement Learning for Obstacle Avoidance Postures for a Hyper-Redundant Manipulator},

author = {Keishi Hirade, Ryuma Niiyama},

year  = {2025},

date = {2025-01-22},

urldate = {2025-01-22},

abstract = {Redundant robots with more degrees of freedom than necessary for given tasks have attracted attention due to their flexibility, but they also increase the complexity of control. Especially for highly redundant robots, accurate motion planning and obstacle avoidance remain challenging. This research aims to develop a redundant robot arm that can perform reaching tasks while avoiding randomly appearing obstacles using reinforcement learning. We adopted the Proximal Policy Optimization (PPO) algorithm and conducted simulations in the Mujoco environment. The learning process consisted of a three-stage curriculum: reaching task, fixed obstacle avoidance, and random obstacle avoidance, gradually increasing difficulty to achieve efficient learning. Experimental results showed that the arm could adapt to complex environments and effectively reach target positions while avoiding obstacles. In particular, the system demonstrated high adaptability to randomly placed obstacles, successfully reaching within a maximum distance of approximately 0.07 m from the target position.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Kawashima2025_SII,

title = {Motion Assistance System for Telesports by Seamlessly Blending Manual and Automatic Throwing Controls},

author = {Yusuke Kawashima, Ryuma Niiyama},

year  = {2025},

date = {2025-01-24},

urldate = {2025-01-24},

abstract = {Telesport, which involves playing sports via avatar robots, has the potential to provide people with physical limitations with the chance to participate in sports, as it allows them to replace their bodies with robots. However, the delay in the teleoperation system makes real-time operation difficult, and it is challenging to operate the agile robot as intended. In this study, we focused on overhand throwing and treated the problem of it being difficult to throw the ball in the intended direction and speed using manual control. In order to accurately realise the agile movements that a user intends, we propose an assistance system that intervenes with automatic control based on the estimated future user's intent for manual control. Furthermore, this assistance system blends manual and automatic control seamlessly to prevent the user from feeling disconnected from the robot due to the intervention of automatic control. The assistance system was evaluated by measuring the direction and speed of the ball thrown overhand, and by assessing whether the user's intent was reflected. As a result, by making the assistance system effective, manual and automatic control were seamlessly blended, and it was confirmed that the throwing motion intended by the user was accurately reflected in the robot.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Uchiyama2024_SII,

title = {Multi-DOF Blower-Powered and Inner Tendon-Driven Soft Inflatable Robotic Arm},

author = {Katsu Uchiyama, Masayuki Otsuka, Ryuma Niiyama},

doi = {10.1109/SII58957.2024.10417544},

year  = {2024},

date = {2024-01-08},

urldate = {2024-01-08},

abstract = {We propose a soft inflatable robotic arm as a type of inflatable robot that is light and can be made larger. This robotic arm is based on a soft inflatable joint, which is actuated by an internal tendon and constantly supplied with air by a blower. The tendon drive method was unknown, so it was difficult to make the arm articulated. To achieve multiple degrees of freedom, a guide was fabricated to prevent tendon interference and to guide the tendons. This guide was made of a thin plate so that the flexibility and light weight of the inflatable robot would not be compromised. Guide was provided at the joints to derive the relationship between joint angle and amount of wire pulling. It was used to maintain the relationship between the tendon wire intersections and the anchor points between the joints. The function of the guide was fully confirmed through motion experiments on a robot arm using these guides. Based on this, a robot arm over 1-meter long was created, and it was verified that various postures were possible. These results will contribute to expanding the design space for low-pressure, large inflatable robots.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Uchiyama2024_IROS,

title = {Pneumatic Bladder Links with Wide Range of Motion Joints for Articulated Inflatable Robots},

author = {Katsu Uchiyama, Ryuma Niiyama},

doi = {10.1109/IROS58592.2024.10802836},

year  = {2024},

date = {2024-10-18},

urldate = {2024-10-18},

booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},

pages = {FrPI6T2.13},

abstract = {Exploration of various applications is the frontier of research on inflatable robots. We proposed an articulated robots consisting of multiple pneumatic bladder links connected by rolling contact joints called Hillberry joints. The bladder link is made of a double-layered structure of tarpaulin sheet and polyurethane sheet, which is both airtight and flexible in shape. The integration of the Hilberry joint into an inflatable robot is also a new approach. The rolling contact joint allows wide range of motion of ±150°, the largest among the conventional inflatable joints. Using the proposed mechanism for inflatable robots, we demonstrated moving a 500 g payload with a 3-DoF arm and lifting 3.4 kg and 5 kg payloads with 2-DoF and 1-DoF arms, respectively. We also experimented with a single 3-DoF inflatable leg attached to a dolly to show that the proposed structure worked for legged locomotion.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{Tezuka2024_Robosoft,

title = {Real-to-real motor learning of tendon-driven soft caterpillar locomotion with world model},

author = {Koichi Tezuka, Ryuma Niiyama},

doi = {10.1109/RoboSoft60065.2024.10521932},

year  = {2024},

date = {2024-04-16},

urldate = {2024-04-16},

abstract = {Controlling soft mobile robots that perform limb-less locomotion is costly to develop due to the need to consider friction and the complexity of movement mechanics. There are methods using reinforcement learning (RL) to create controllers for complex soft caterpillar robots. However, these often involve learning through simulation, and model inaccuracies can lead to reduced controller performance upon deployment. In this paper, we created a soft caterpillar robot driven by tendons with two motors and trained a controller using RL. By training with real soft robots without using simulations, we created a learning model that works effectively even with soft robots' complex dynamics, without performance degradation upon deployment. Using a model-based learning algorithm enabled quick policy learning, even with real robots that typically require time-consuming sampling. The learning model we developed could achieve locomotion in forward tasks after about one hour of training. After training, the actual robot was capable of moving at approximately 36.7 mm/s. To the best of our knowledge, this is the first instance of learning locomotion for a soft mobile robot's crawling using only a real robot.},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}