Bio-inspired Control Approach Research Articles

Acinonyx jubatus-Inspired Quadruped Robotics: Integrating Neural Oscillators for Enhanced Locomotion Control.

This study presents the design, simulation, and prototype creation of a quadruped robot inspired by the Acinonyx jubatus (cheetah), specifically designed to replicate its distinctive walking, trotting, and galloping locomotion patterns. Following a detailed examination of the cheetah's skeletal muscle anatomy and biomechanics, a simplified model of the robot with 12 degrees of freedom was conducted. The mathematical transformation hierarchy model was established, and direct kinematics were simulated. A bio-inspired control approach was introduced, employing a Central Pattern Generator model based on Wilson-Cowan neural oscillators for each limb, interconnected by synaptic weights. This approach assisted in the simulation of oscillatory signals for relative phases corresponding to four distinct gaits in a system-level simulation platform. The design phase was conducted using CAD software (SolidWorks 2018), resulting in a 1:3-scale robot mirroring the cheetah's actual proportions. Movement simulations were performed in a virtual mechanics software environment, leading to the construction of a prototype measuring 35.5 cm in length, 21 cm in width, 27 cm in height (when standing), and weighing approximately 2.1 kg. The experimental validation of the prototype's limb angular positions and trajectories was achieved through the image processing of video-recorded movements, demonstrating a high correlation (0.9025 to 0.9560) in joint angular positions, except for the knee joint, where a correlation of 0.7071 was noted. This comprehensive approach from theoretical analysis to practical implementation showcases the potential of bio-inspired robotics in emulating complex biological locomotion.

A bio-inspired emergent control approach for distributed processes

The complexity of industrial processes has grown exponentially, with high degrees of dependency, non-linearity, imprecision, among other aspects, which motivates the interest in developing distributed control systems for their management. In this sense, this work proposes a bio-inspired distributed control approach, where control actions emerge from the component interactions. The distributed control approach is based on the response threshold model to solve the control problem by imitating the behavior of ants. Particularly, our approach is inspired by the way as the ants carry out the division of labor in a colony. Thus, our control approach based on the threshold response model refers to the possibility of reacting to stimuli associated with the distributed control tasks. It has the ability to stabilize the process in the presence of abrupt/successive changes and various initial conditions, with a minimum effort of the actuators to achieve the objectives. Also, it has shown its versatility in different operational contexts with the same parameter tuning. The bio-inspired control approach is proved in a quadruple tank process, a complex system due to its multivariate nature. In this way, our paper introduces a new domain of application of the response threshold model in industrial processes. Several experiments were carried out in different contexts to evaluate its stability, robustness, etc., and compare it with other similar works. In general, the control performance metrics show satisfactory results, which reflects its ability to adapt to changes in the dynamics of the process, which encourages additional studies.

Neuromechanical force-based control of a powered prosthetic foot.

This article presents a novel neuromechanical force-based control strategy called FMCA (force modulated compliant ankle), to control a powered prosthetic foot. FMCA modulates the torque, based on sensory feedback, similar to neuromuscular control approaches. Instead of using a muscle reflex-based approach, FMCA directly exploits the vertical ground reaction force as sensory feedback to modulate the ankle joint impedance. For evaluation, we first demonstrated how FMCA can predict human-like ankle torque for different walking speeds. Second, we implemented the FMCA in a neuromuscular transtibial amputee walking simulation model to validate if the approach can be used to achieve stable walking and to compare the performance to a neuromuscular reflex-based controller that is already used in a powered ankle. Compared to the neuromuscular model-based approach, the FMCA is a simple solution with a sufficient push-off that can provide stable walking. Third, to assess the ability of the FMCA to generate human-like ankle biomechanics during walking at the preferred speed, we implemented this strategy in a powered prosthetic foot and performed experiments with a non-amputee subject. The results confirm that, for this subject, FMCA can be used to mimic the non-amputee reference ankle torque and the reference ankle angle. The findings of this study support the applicability and advantages of a new bioinspired control approach for assisting amputees. Future experiments should investigate the applicability to other walking speeds and the applicability to the target population.

Control of a muscle-like soft actuator via a bioinspired approach

Soft actuators have played an indispensable role in generating compliant motions of soft robots. Among the various soft actuators explored for soft robotic applications, dielectric elastomer actuators (DEAs) have caught the eye with their intriguing attributes similar to biological muscles. However, the control challenge of DEAs due to their strong nonlinear behaviors has hindered the development of DEA-based soft robots. To overcome the control challenge, this paper proposes a bioinspired control approach of DEAs. A three-dimensional muscle-like DEA, capable of large forces and giant deformation, is fabricated and adopted as the control platform. To facilitate the controller design, the dynamic model of the DEA is developed through experimental analysis, which takes electromechanical coupling, viscoelastic effects and dynamics uncertainties into consideration. Motivated by the proprioception of the biological muscles, the self-sensing capability of the actuator is explored and exhibits good accuracy. Thus the self-sensing of the actuator is utilized to provide the sensory feedback in the control loop without the need of additional external sensors. Inspired from the role of the cerebellum in motor learning, a cerebellum model articulation nonlinear controller is proposed to compensate the dynamics uncertainties and to provide motion correction. Finally, the effectiveness of the proposed control approach is verified by both the simulation and the experiments.

Novel bioinspired control approaches to increase the stiffness variability in multi-muscle driven joints

Antagonistic muscle pairs pulling on a joint are in general able to modulate stiffness through co-activation. Closer analysis of the stiffness, however, shows that, depending on the muscle and joint parameters, domains might occur in joint angle space for which stiffness variation is limited (low stiffness variability) or even impossible (stiffness nodes). As a consequence, stiffness control utilizing pure co-activation might fail. This work presents novel strategies for simultaneous control of torque and stiffness in a hinge joint actuated by two antagonistic muscle pairs. One strategy handles stiffness nodes by shifting them away from the current joint position and thus regaining stiffness controllability. To prevent domains of low stiffness variation, an optimal muscle configuration is sought and finally defined which allows for a maximal stiffness variation across a wide joint angle range. Based on this optimal configuration, four additional control strategies are proposed and tested which deliver stiffnesses and torques comparable to those obtained in the optimal case. The strategies combine torque control and stiffness control by co-activation with novel ideas like activation overflow and an inverse model approach. All strategies are tested in simulation and the results are compared with those of the optimal setup.

Bio-Inspired Control of an Arm Exoskeleton Joint with Active-Compliant Actuation System

This paper presents the methodology followed on the design of a multi-contact point haptic interface that uses a bio-inspired control approach and a novel actuation system. The combination of these components aims at creating a system that increases the operability of the target, and, at the same time, enables an intuitive and safe tele-operation of any complex robotic system of any given morphology. The novelty lies on the combination of a thoughtful kinematic structure driven by an active-compliant actuation system and a bio-inspired paradigm for its regulation. Due to the proposed actuation approach, the final system will achieve the condition of wearable system. On that final solution, each joint will be able to change its stiffness depending on the task to be executed, and on the anatomical features of each individual. Moreover, the system provides a variety of safety mechanisms at different levels to prevent causing any harm to the operator. In future, the system should allow the complete virtual immersion of the user within the working scenario.