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1. A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements

   https://doi.org/10.1038/s41598-022-11102-1  

   Ramadan, Rachid ; Geyer, Hartmut ; Jeka, John ; Schöner, Gregor ; Reimann, Hendrik ( May 2022 , Scientific Reports)

   Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

    

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2. A Potential Energy Shaping Controller with Ground Reaction Force Feedback for a Multi-Activity Knee-Ankle Exoskeleton

   https://doi.org/10.1109/BioRob49111.2020.9224341  

   Divekar, Nikhil V. ; Lin, Jianping ; Nesler, Christopher ; Borboa, Sara ; Gregg, Robert D. ( November 2020 , 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob))

   This paper presents the design and implementation of a novel multi-activity control strategy for a backdrivable knee-ankle exoskeleton. Traditionally, exoskeletons have used trajectory-based control of highly geared actuators for complete motion assistance. In contrast, we develop a potential energy shaping controller with ground reaction force (GRF) feedback that facilitates multi-activity assistance from a backdrivable exoskeleton without prescribing pre-defined kinematics. Although potential energy shaping was previously implemented in an exoskeleton to reduce the user’s perceived gravity, this model-based approach assumes the stance leg is fully loaded with the weight of the user, resulting in excessive control torques as weight transfers to the contralateral leg during double support. The presented approach uses GRF feedback to taper the torque control output for any activity involving multiple supports, leading to a closer match with normative joint moments in simulations based on pre-recorded human data during level walking. To implement this strategy, we present a custom foot force sensor that provides GRF feedback to the previously designed exoskeleton. Finally, results from an able-bodied human subject experiment demonstrate that the exoskeleton is able to reduce muscular activation of the primary muscles related to the knee and ankle joints during sit-to-stand, stand-to-sit, level walking, and stair climbing. 

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3. Applying Artificial Intelligence to Optimize Small-Scale Ocean Current Turbine Performance

   https://doi.org/10.1115/IMECE2022-95804  

   Rouhi, Shahab ; Sadeqi, Setare ; Xiros, Nikolaos ; Birk, Lothar ; Aktosun, Erdem ; Ioup, Juliette ( October 2022 , American Society of Mechanical Engineers)

   A comprehensive artificial intelligence-based motor drive was developed to control the performance of a permanent magnet direct current (PMDC) motor employed as a small-scale three-bladed horizontal axis ocean current turbine. Although the conventional controller performs reasonably in a lab environment where non-linear load is absented; however, for towing tank experiments with noisy and potentially non-linear input, it is crucial to run the small-scale turbine in a robust mode. A mathematical model of a PMDC motor dynamic system is derived incorporating a fuzzy logic controller. In addition, this drive control was validated experimentally. The experimental design is discussed in detail. The system performance was tested experimentally over a wide range of operating condition to validate the fuzzy logic control robustness and effectiveness. Also, it is shown that the speed of the PMDC motor was controlled by using this fuzzy logic controller. The speed tracking shows good agreement with the reference speed regardless of the load condition.

    

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4. A Unified Optimization Framework and New Set of Performance Metrics for Robot Leg Design

   Semasinghe, C. ; Taylor, D. ; Rezazadeh, S. ( January 2021 , IEEE International Conference on Robotics and Automation)

   null (Ed.)

   This work presents a framework for the simultaneous optimization of motors, transmissions, and mechanisms of different joints of robotic legs with the goal of achieving an energy efficient, precisely controllable and stable locomotion in dynamic environments. This unified framework allowed us to introduce and formulate new performance metrics for the separate evaluation of the system’s stabilizing ability during stance and swing. Moreover, through a case study, this design optimization framework was applied to an anthropomorphic robot leg model and the optimal actuation configurations for the leg were obtained. This case study also helped us investigate the relationships among our three objectives (energy efficiency, and stance and swing control). It was shown that while in some cases a clear trade-off exists, it is not always valid and as such, careful consideration of all three objectives is necessary. 

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5. Feedback Control of the Locomotion of a Tailed Quadruped Robot

   https://doi.org/10.1115/DETC2021-71611  

   Liu, Yujiong ; Ben-Tzvi, Pinhas ( August 2021 , ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 45TH MECHANISMS AND ROBOTICS CONFERENCE (MR))

   The traditional locomotion paradigm of quadruped robots is to use dexterous (multi degrees of freedom) legs and dynamically optimized footholds to balance the body and achieve stable locomotion. With the introduction of a robotic tail, a new locomotion paradigm becomes possible as the balancing is achieved by the tail and the legs are only responsible for propulsion. Since the burden on the leg is reduced, leg complexity can be also reduced. This paper explores this new paradigm by tackling the dynamic locomotion control problem of a reduced complexity quadruped (RCQ) with a pendulum tail. For this specific control task, a new control strategy is proposed in a manner that the legs are planned to execute the open-loop gait motion in advance, while the tail is controlled in a closed-loop to prepare the quadruped body in the desired orientation. With these two parts working cooperatively, the quadruped achieves dynamic locomotion. Partial feedback linearization (PFL) controller is used for the closed-loop tail control. Pronking, bounding, and maneuvering are tested to evaluate the controller’s performance. The results validate the proposed controller and demonstrate the feasibility and potential of the new locomotion paradigm. 

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