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Miyamae H, Hori K, Uchida M (2021) Control system using time-state control form for balloon robot. IEE J Trans Electr Electron Eng 16:412–418
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The drag force disrupts BALLU’s walking motion because of the balloon’s large cross-section. This adds additional complexity to the already nonlinear dynamics of the rigid body. The large fluctuation makes it even harder to analyze. The magnitude is about 5.5% compared to its body weight and can peak up to about 12.0%. Moreover, there are multiple sources of uncertainty on the platform. For example, while it is necessary to adopt lightweight and affordable parts, smaller and low-cost sensors and actuators tend to have lower fidelity. In addition, light materials are prone to wear, and helium balloons lose their buoyancy over time, which makes the system time-varying and the identified parameters unknown. F hip, r is the force from the leg at the hip in the radial direction connecting the hip and the foot, and F hip, t is in the tangential direction.
7 Conclusion
O’Halloran, A., O’Malley, F. & McHugh, P. A review on dielectric elastomer actuators, technology, applications, and challenges. Journal of Applied Physics 104, 071101, https://doi.org/10.1063/1.2981642 (2008). All data for analysis were collected in simulation. Not only was nominal walking data from teleoperation collected, but walking sequences that include intentionally elongated and shortened double and single support phases as well as following recovery from such abnormal timings were also recorded. Bevan, R. & Rutter, M. Colorectal cancer screening—who, how, and when? Clin Endosc 51, 37–49, https://doi.org/10.5946/ce.2017.141 (2018). The current system is set up for easy and modular development, as various processes are concurrently running on board, including the motor controller and the communication and messaging module. Shared memory is leveraged to share data between processes. Python is primarily used for simplicity, while C++ is used for low-level modules. 2.3 Simulation Environment
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While these platforms have shown remarkable progress in technology, essential yet often overlooked aspects that are contributing to their full deployment in close proximity to humans are safety and cost. When they malfunction, the heavyweight and powerful actuation methods could act as a potential cause of serious damage to its surrounding environments and even threaten human lives. In the context of service robots, such robots’ capacity might be redundant for common needs in everyday life but also dangerous. We presented a statistical method that can extract a state vector from data collected from the highly nonlinear dynamics, using Spearman Correlation Coefficient. The state vector is low dimensional yet contains essential information of the high dimensional system. Franchetti, M. & Kress, C. An economic analysis comparing the cost feasibility of replacing injection molding processes with emerging additive manufacturing techniques. The International Journal of Advanced Manufacturing Technology 88, 2573–2579, https://doi.org/10.1007/s00170-016-8968-7 (2017).
Author Contributions
Ghassemi and Hong (2016) introduced the first iteration of BALLU to verify the concept of buoyancy assisted legged robot, but it was limited to teleoperation using radio control signals. In this paper, the next iteration, BALLU2, which is the first implementation that can walk by algorithms, is presented with details on its design and controller. The contributions of this work are as follows: Yoon J, Lee J (2017) Altitude and roll control of a hovering quad-rotor air vehicle using the multi-objective approximate optimization of proportional–integral–differential control. Eng Optim 49(10):1704–1718 Huang, C. et al. Miniaturized swimming soft robot with complex movement actuated and controlled by remote light signals. Scientific reports 5, 17414, https://doi.org/10.1038/srep17414 (2015). We improved the platform and built a new version, BALLU2, which has a simpler and more robust design. The onboard computer newly adopted allows BALLU2 to be controlled by an algorithm.
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Touching on safety, it is also evident that BALLU can only produce so much force and momentum in any given direction. In its walking direction, the maximum acceleration and velocity is approximately 0.3m/ s 2 and 0.4m/ s, where the mass of the entire robot is only about 170 g. Even then, because of the balloon body’s radius, the first point of collision in a human environment will likely be the balloons and not the legs. This shows that even if a system like BALLU were to malfunction and collide, it will cause no harm to its surrounding environment or humans. 7 Conclusion The pelvis link is what holds the legs and the balloons together, and is also the mount for BALLU’s onboard controller. A Raspberry Pi Zero W is used for its low-cost, lightweight, potential onboard computing, and flexible communication (e.g. WiFi and Bluetooth) capabilities. These updates are a distinct difference from the previous version ( Ghassemi and Hong, 2016), which was limited to teleoperation via radio controllers, and allows BALLU2 to walk based on algorithms.We trained a planar data-driven walking controller with artificial neural networks using the definition of the state and a set of expert data. Aymerich-Franch, L., and Ferrer, I. (2020). Social robots as a brand strategy. In Innovation in Advertising and Branding Communication (UK. Routledge). 86–102. doi:10.4324/9781003009276-6
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