Int-Ball: Crew-Supportive Autonomous Mobile Camera Robot on ISS/JEM

Mitani, Shinji; Goto, Masayuki; Konomura, Ryo; Yoshida, Shoji; Hagiwara, Keiji; Shigeto, Shuhei; Tanishima, Nobutaka

doi:10.1109/aero.2019.8741689

Cited by 33 publications

(3 citation statements)

References 6 publications

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“…By utilizing propellant gases or fans to generate the reaction forces, small robots can move inside the tridimensional space of the ISS thanks to the negligible gravity. Astrobee [10], CIMON [11] and Int-Ball [12] are some successful examples of free-flying robots with autonomous mobility and task-performing capabilities operating in the ISS.…”

Section: A Related Workmentioning

confidence: 99%

RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity

Ribeiro¹,

Uno²,

Masazumi³

et al. 2023

Preprint

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Robotic mobility in microgravity is necessary to expand human utilization and exploration of outer space. Bio-inspired multi-legged robots are a possible solution for safe and precise locomotion. However, a dynamic motion of a robot in microgravity can lead to failures due to gripper detachment caused by excessive motion reactions. We propose a novel Reaction-Aware Motion Planning (RAMP) to improve locomotion safety in microgravity, decreasing the risk of losing contact with the terrain surface by reducing the robot's momentum change. RAMP minimizes the swing momentum with a Low-Reaction Swing Trajectory (LRST) while distributing this momentum to the whole body, ensuring zero velocity for the supporting grippers and minimizing motion reactions. We verify the proposed approach with dynamic simulations indicating the capability of RAMP to generate a safe motion without detachment of the supporting grippers, resulting in the robot reaching its specified location. We further validate RAMP in experiments with an air-floating system, demonstrating a significant reduction in reaction forces and improved mobility in microgravity.

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Section: A Related Workmentioning

confidence: 99%

RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity

Ribeiro¹,

Uno²,

Masazumi³

et al. 2023

Preprint

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“…A number of other robot solutions have been built or proposed for the environments and missions listed above. In microgravity, such as on a space station, small assistive free-flyers such as Astrobee [9], Int-Ball [10], and CIMON [11] achieve precise mobility, but their weak thrusters cannot apply high loads or support maneuvering with large, high-powered attached manipulators. This limits both their anchored reach and forceful manipulation capability, making many key station servicing tasks infeasible.…”

Section: Related Workmentioning

confidence: 99%

ReachBot: A Small Robot for Large Mobile Manipulation Tasks

Schneider¹,

Bylard²,

Chen³

et al. 2021

Preprint

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“…Synchronized Position Hold Engage and Reorient Experimental Satellite (SPHERES) [4] was successfully applied to the international space station in 2006, providing scientists with a zero-gravity, three-dimensional mobile test platform. Internal Ball Camera (Int-ball) [5] was developed by the Japan aerospace exploration agency and has been put into use on the international space station in 2017. Astrobee [6] was sent to the international space station in 2019, which supported remote control or manual control, and was used to read mission sensor data and monitor the activities of all crew members.…”

Section: A Backgroundmentioning

confidence: 99%

Hierarchical Attention-Based Astronaut Gesture Recognition: A Dataset and CNN Model

Zhang

Wang

2020

IEEE Access

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In the space station, visual gesture recognition is an important component for gesture based human-robot interaction to control the robot, which assists astronauts to complete simple, repetitive and cooperative work. However, public gesture datasets are captured in the daily environment and existing approaches trained on these datasets achieve imprecise performance for astronaut gesture recognition. In this paper, we introduce a new astronaut gesture dataset (DSSL-Astronaut gesture dataset) and a novel hierarchical attention single-shot detector network (HA-SSD) for astronaut gesture recognition. Specifically, this dataset consists of the real and augmented images. The real images captured in the simulated space station are closed to the real images in the space station environment. Meanwhile, we utilize the Mask-RCNN model to segment the foreground image including an astronaut from real data and capture the background images of the simulated space station at different views and illuminations. Then we combine them to synthesize the augmented images. A novel HA-SSD model consists of a lightweight backbone named MobileNet and a hierarchical attention mechanism. The MobileNet is used as the feature extractor, which contains several depth-wise separable convolutions to make a trade-off between latency and accuracy. Meanwhile, the hierarchical channel-wise attention module is adopted to exploit the fine semantic information to enrich the features for improving the performance of gesture recognition. We conduct experiments to demonstrate that our dataset is suitable for the space station and our approach is able to effectively localize and recognize the gestures with strong generality.

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Int-Ball: Crew-Supportive Autonomous Mobile Camera Robot on ISS/JEM

Cited by 33 publications

References 6 publications

RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity

RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity

ReachBot: A Small Robot for Large Mobile Manipulation Tasks

Hierarchical Attention-Based Astronaut Gesture Recognition: A Dataset and CNN Model

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