@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}

}