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1. Modeling and Control of a Bioinspired, Distributed Electromechanical Actuator System Emulating a Biological Spine

   https://doi.org/10.1109/TMECH.2024.3409696  

   Ku, Bonhyun; Banerjee, Arijit (January 2024, IEEE/ASME Transactions on Mechatronics)

   The robotic spine has a lot of potential for snake-like, quadruped, and humanoid robots, as it can improve their mobility, flexibility, and overall function. A common approach to developing an articulated spine uses geared motors to imitate vertebrae. Instead of using geared motors that rotate 360 degree, a bioinspired gearless electromechanical actuator was proposed and developed as an alternative, specifically for humanoid spine applications. The actuator trades off angular flexibility for torque, while the geared motor trades off speed for torque. This article compares the proposed actuator and conventional geared motors regarding torque, acceleration, and copper loss for a vertebra's angular flexibility. When its angular flexibility is lower than 14∘, the proposed actuator achieves higher torque capability without gears than with conventional motors. Lower angular flexibility, which means smaller airgaps, allows the proposed actuator to produce a much stronger torque for the same input power. The actuator's nonlinear electrical and mechanical dynamics models are developed and used for position control of a six-module distributed spine. In addition, two different position-control architectures are developed: an outer loop proportional-integral (PI) position controller with an inner loop PI current controller and an outer loop PI position controller with an inner loop PI torque controller. 

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2. Human–Exoskeleton Coupling Simulation for Lifting Tasks with Shoulder, Spine, and Knee-Joint Powered Exoskeletons

   https://doi.org/10.3390/biomimetics9080454  

   Arefeen, Asif; Xia, Ting; Xiang, Yujiang (August 2024, Biomimetics)

   In this study, we introduce a two-dimensional (2D) human skeletal model coupled with knee, spine, and shoulder exoskeletons. The primary purpose of this model is to predict the optimal lifting motion and provide torque support from the exoskeleton through the utilization of inverse dynamics optimization. The kinematics and dynamics of the human model are expressed using the Denavit–Hartenberg (DH) representation. The lifting optimization formulation integrates the electromechanical dynamics of the DC motors in the exoskeletons of the knee, spine, and shoulder. The design variables for this study include human joint angle profiles and exoskeleton motor current profiles. The optimization objective is to minimize the squared normalized human joint torques, subject to physical and task-specific lifting constraints. We solve this optimization problem using the gradient-based optimizer SNOPT. Our results include a comparison of predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles between lifting tasks with and without exoskeleton assistance. We also explore various combinations of exoskeletons for the knee, spine, and shoulder. By resolving the lifting optimization problems, we designed the optimal torques for the exoskeletons located at the knee, spine, and shoulder. It was found that the support from the exoskeletons substantially lowers the torque levels in human joints. Additionally, we conducted experiments only on the knee exoskeleton. Experimental data indicated that using the knee exoskeleton decreases the muscle activation peaks by 35.00%, 10.03%, 22.12%, 30.14%, 16.77%, and 25.71% for muscles of the erector spinae, latissimus dorsi, vastus medialis, vastus lateralis, rectus femoris, and biceps femoris, respectively. 

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3. Cybersecurity Vulnerabilities in Two Artificially Intelligent Humanoids on the Market

   Kinzler, Matt; Miller, Justin; Wu, Zhou; Williams, Andrew; Perouli, Debbie (April 2019, Workshop on Technology and Consumer Protection (ConPro ‘19), held in conjunction with the 40th IEEE Symposium on Security and Privacy)

   As artificially intelligent humanoids become increasingly prevalent in the home, it is imperative that we develop secure designs to guard against cyberattacks. The next evolution of AI-powered home devices, such as Alexa, is to create physical effectors to enable these devices to alter their environments. Current humanoids on the market, such as the EZ-Robot JD and NAO, are examples of artificially intelligent robots that may one day become common in home environments. If these humanoids are not designed to be safe against cybersecurity vulnerabilities, they may be used to cause harm to living spaces and possibly even the humans living in these spaces. This paper examines the cybersecurity of two humanoid robots and provides recommendations for future safe designs and protections in artificial intelligent social robots. 

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4. Hierarchical World Models as Visual Whole-Body Humanoid Controllers

   Hansen, Nicklas; V, Jyothir S; Sobal, Vlad; LeCun, Yann; Wang, Xiaolong; Su, Hao (April 2025, The International Conference on Learning Representations (ICLR 2025))

   Whole-body control for humanoids is challenging due to the high-dimensional nature of the problem, coupled with the inherent instability of a bipedal morphology. Learning from visual observations further exacerbates this difficulty. In this work, we explore highly data-driven approaches to visual whole-body humanoid control based on reinforcement learning, without any simplifying assumptions, reward design, or skill primitives. Specifically, we propose a hierarchical world model in which a high-level agent generates commands based on visual observations for a low-level agent to execute, both of which are trained with rewards. Our approach produces highly performant control policies in 8 tasks with a simulated 56-DoF humanoid, while synthesizing motions that are broadly preferred by humans. 

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5. Effect of electromechanical coupling on locally resonant quasiperiodic metamaterials

   https://doi.org/10.1063/5.0119914  

   LeGrande, Joshua; Bukhari, Mohammad; Barry, Oumar (January 2023, AIP Advances)

   Electromechanical metamaterials have been the focus of many recent studies for use in simultaneous energy harvesting and vibration control. Metamaterials with quasiperiodic patterns possess many useful topological properties that make them a good candidate for study. However, it is currently unknown what effect electromechanical coupling may have on the topological bandgaps and localized edge modes of a quasiperiodic metamaterial. In this paper, we study a quasiperiodic metamaterial with electromechanical resonators to investigate the effect on its bandgaps and localized vibration modes. We derive here the analytical dispersion surfaces of the proposed metamaterial. A semi-infinite system is also simulated numerically to validate the analytical results and show the band structure for different quasiperiodic patterns, load resistors, and electromechanical coupling coefficients. The topological nature of the bandgaps is detailed through an estimation of the integrated density of states. Furthermore, the presence of topological edge modes is determined through numerical simulation of the energy harvested from the system. The results indicate that quasiperiodic metamaterials with electromechanical resonators can be used for effective energy harvesting without changes in the bandgap topology for weak electromechanical coupling. 

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