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Unlike the previously mentioned platforms that rely on passively acting forces (e.g., buoyancy in the case with helium balloons), there are also works that have directly integrated active thrusters. The concept of a bipedal robot supported by a propulsion system is first proposed by Zhang et al. (2016). Aerial-biped by Maekawa et al. (2018) is a bipedal robot attached to a quadrotor, and the robot walks using a gait sequence generated by a policy learned by reinforcement learning. Though it is not published, LEONARDO from Aerospace Robotics and Control at Caltech (2019) is another bipedal robot with drone-like propellers. On a more extreme note, the feasibility of a combination of propellers, buoyancy force, and active rappelling to lift rigid bodies has also been studied by Lin et al. (2019). Schreuders, E. H., Grobbee, E. J., Spaander, M. C. W. & Kuipers, E. J. Advances in fecal tests for colorectal cancer screening. Current treatment options in gastroenterology 14, 152–162, https://doi.org/10.1007/s11938-016-0076-0 (2016).
BALLU2: A Safe and Affordable Buoyancy Assisted Biped
If BALLU’s feet are behind the center of the pelvis during the double support phase, the horizontal components of the two legs are effectively aligned and the robot can induce a large acceleration. However, this has a risk, as the robot can fall into the aforementioned sink-down state if it holds this state for too long.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. Incheon Airport (2019). [Incheon Airport] 2019 Incheon International Airport Promotional Video. [YouTube video]. [Accessed Jun. 19, 2021].
Balloon Dino | Smyths Toys UK Squeakee The Interactive Balloon Dino | Smyths Toys UK
Manfredi, L., Yue, L., Zhang, J. & Cuschieri, A. A 4 DOFs variable stiffness soft module. In IEEE RoboSoft, https://doi.org/10.1109/ROBOSOFT.2018.8404903 (2018). Manfredi, L., Yue, L. & Cuschieri, A. A 3 DOFs mini variable stiffness soft pneumatic actuator. In Proc. ACTUATOR 2018; 16th Int. Conf. New Actuators, 1–4 (2018). As a second modification, two unachievable velocities were commanded. When the commanded velocity is too low ( Figures 9G,H), it can be observed that the controller takes tiny steps. As a result, the two feet become closer and the lines connecting each foot and the pelvis get towards the vertical so to minimize the forward force. It can be interpreted that the controller tries to take the minimum length of single support phases not to increase speed (Section 3.3.2). As the controller drives the body rather upward, the average height is higher than the nominal condition. Contrarily, the controller takes big steps when the commanded velocity is too high ( Figures 9I,J). It is to take single support phases to catch up with the high commanded velocity. Since the controller takes single support phases as much as it can, the average body height is lower than that under the nominal condition. 6.3 Hardware TestThe original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding authors. Author Contributions
Robot Balloon - Etsy UK Robot Balloon - Etsy UK
BALLU has only 2 DoF for each leg and only 1 active DoF on the knee because the hip joint is passive and freely rotates. Unlike the majority of robots that can follow the desired trajectory generated by a controller, passive dynamics govern BALLU’s hip joints and the controller has to realize the desired motion considering that the hip joint can only swing freely. 3.1.2 Nonlinear Dynamics Liu Y, Dong HB, Lohse N, Petrovic S (2016) A multi-objective genetic algorithm for optimization of energy consumption and shop floor production performance. Int J Prod Econ 179:259–272 Marchese, A. D., Katzschmann, R. K. & Rus, D. A recipe for soft fluidic elastomer robots. Soft Robotics 1, 7–25, https://doi.org/10.1089/soro.2014.0022 (2015). 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).Bledt, G., Powell, M. J., Katz, B., Di Carlo, J., Wensing, P. M., and Kim, S. (2018). Mit cheetah 3: Design and control of a robust, dynamic quadruped robot. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2245–2252. New Jersey, IEEE. doi:10.1109/IROS.2018.8593885 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 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 The simulation result was taken as the drag coefficient at a pitch and yaw pair since it is computed with unit speed. In the dynamics simulation, the drag force is computed using the model and applied as an opposing force in the simulation. 3 Motion Analysis The network is trained for 100 epochs with early stopping. For each set of hyperparameters, they are mostly stopped in less than 50 epochs. Dataset was randomly split so that 70% of data is used for training, 15% for validation, 15% for testing, and the training and validation set is shuffled at every epoch.
balloon robot using time-state Trajectory generation for balloon robot using time-state
Appleyard, M. N. et al. The measurement of forces exerted during colonoscopy. Gastrointestinal Endoscopy 52, 237–240, https://doi.org/10.1067/mge.2000.107218 (2000).In practice, as injecting the same amount of helium every time to keep the body afloat is difficult, a generous amount of helium is initially injected, and counterweights are attached to the body to adjust the net upward force. This is done by calibrating the robot’s normal weight on a scale, which is empirically chosen to be 55 gf in the presented version of BALLU. Such a choice allows the robot to stay vertically upright when in a double support phase, but sink when in a single support phase, which will be important in the subsequent locomotion approach. 2.1.2 Pelvis Link
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