Design of Low-Cost Modular Bio-Inspired Electric-Pneumatic Actuator (EPA)-Driven Legged Robots.

Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in electric-pneumatic actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monoped robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, (1) provide opportunities to study different locomotor subfunctions-stance, swing, and balance; (2) help investigate the role of actuation schemes in tasks such as hopping and walking; and (3) allow testing hypotheses regarding biological locomotors in real-world physical test benches.

Role of compliant mechanics and motor control in hopping - from human to robot.

Compliant leg function found during bouncy gaits in humans and animals can be considered a role model for designing and controlling bioinspired robots and assistive devices. The human musculoskeletal design and control differ from distal to proximal joints in the leg. The specific mechanical properties of different leg parts could simplify motor control, e.g., by taking advantage of passive body dynamics. This control embodiment is complemented by neural reflex circuitries shaping human motor control. This study investigates the contribution of specific passive and active properties at different leg joint levels in human hopping at different hopping frequencies. We analyze the kinematics and kinetics of human leg joints to design and control a bioinspired hopping robot. In addition, this robot is used as a test rig to validate the identified concepts from human hopping. We found that the more distal the joint, the higher the possibility of benefit from passive compliant leg structures. A passive elastic element nicely describes the ankle joint function. In contrast, a more significant contribution to energy management using an active element (e.g., by feedback control) is predicted for the knee and hip joints. The ankle and knee joints are the key contributors to adjusting hopping frequency. Humans can speed up hopping by increasing ankle stiffness and tuning corresponding knee control parameters. We found that the force-modulated compliance (FMC) as an abstract reflex-based control beside a fixed spring can predict human knee torque-angle patterns at different frequencies. These developed bioinspired models for ankle and knee joints were applied to design and control the EPA-hopper-II robot. The experimental results support our biomechanical findings while indicating potential robot improvements. Based on the proposed model and the robot's experimental results, passive compliant elements (e.g. tendons) have a larger capacity to contribute to the distal joint function compared to proximal joints. With the use of more compliant elements in the distal joint, a larger contribution to managing energy changes is observed in the upper joints.

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without intervening in the driving task. This paper proposes a multi-level drowsiness detection system by a deep neural network-based classification system using a combination of electrocardiogram and respiration signals. The proposed method is based on a combination of convolutional neural networks (CNNs) and long short-term memory (LSTM) networks for classifying drowsiness by concurrently using heart rate variability (HRV), power spectral density of HRV, and respiration rate signal as inputs. Two models, a CNN-based model and a hybrid CNN-LSTM-based model were used for multi-level classifications. The performance of the proposed method was evaluated on experimental data collected from 30 subjects in a simulated driving environment. The performance and the results of both models are presented and compared. The best performance for both three-level and five-level drowsiness classifications was achieved by the CNN-LSTM model. The results indicate that the three-level and five-level classifications of drowsiness can be achieved with 91 and 67% accuracy, respectively.

Exploring the effects of serial and parallel elasticity on a hopping robot.

The interaction between the motor control and the morphological design of the human leg is critical for generating efficient and robust locomotion. In this paper, we focus on exploring the effects of the serial and parallel elasticity on hopping with a two-segmented robotic leg called electric-pneumatic actuation (EPA)-Hopper. EPA-Hopper uses a hybrid actuation system that combines electric motors and pneumatic artificial muscles (PAM). It provides direct access to adjust the physical compliance of the actuation system by tuning PAM pressures. We evaluate the role of the serial and parallel PAMs with different levels of compliance with respect to four criteria: efficiency, performance, stability, and robustness of hopping against perturbations. The results show that the serial PAM has a more pronounced impact than the parallel PAM on these criteria. Increasing the stiffness of the serial PAM decreases the leg stiffness of the unloading phase during hopping. The stiffer the leg, the more efficient and the less robust the movement. These findings can help us further understand the human hopping mechanism and support the design and control of legged robots and assistive devices.

From template to anchors: transfer of virtual pendulum posture control balance template to adaptive neuromuscular gait model increases walking stability.

Biomechanical models with different levels of complexity are of advantage to understand the underlying principles of legged locomotion. Following a minimalistic approach of gradually increasing model complexity based on Template & Anchor concept, in this paper, a spring-loaded inverted pendulum-based walking model is extended by a rigid trunk, hip muscles and reflex control, called nmF (neuromuscular force modulated compliant hip) model. Our control strategy includes leg force feedback to activate hip muscles (originated from the FMCH approach), and a discrete linear quadratic regulator for adapting muscle reflexes. The nmF model demonstrates human-like walking kinematic and dynamic features such as the virtual pendulum (VP) concept, inherited from the FMCH model. Moreover, the robustness against postural perturbations is two times higher in the nmF model compared to the FMCH model and even further increased in the adaptive nmF model. This is due to the intrinsic muscle dynamics and the tuning of the reflex gains. With this, we demonstrate, for the first time, the evolution of mechanical template models (e.g. VP concept) to a more physiological level (nmF model). This shows that the template model can be successfully used to design and control robust locomotor systems with more realistic system behaviours.

Improving suspended sediment measurements by automatic samplers.

Suspended solids either as total suspended solids (TSS) or suspended sediment concentration (SSC) is an integral particulate water quality parameter that is important in assessing particle-bound contaminants. At present, nearly all stormwater runoff quality monitoring is performed with automatic samplers in which the sampling intake is typically installed at the bottom of a storm sewer or channel. This method of sampling often results in a less accurate measurement of suspended sediment and associated pollutants due to the vertical variation in particle concentration caused by particle settling. In this study, the inaccuracies associated with sampling by conventional intakes for automatic samplers have been verified by testing with known suspended sediment concentrations and known particle sizes ranging from approximately 20 µm to 355 µm under various flow rates. Experimental results show that, for samples collected at a typical automatic sampler intake position, the ratio of sampled to feed suspended sediment concentration is up to 6600% without an intake strainer and up to 300% with a strainer. When the sampling intake is modified with multiple sampling tubes and fitted with a wing to provide lift (winged arm sampler intake), the accuracy of sampling improves substantially. With this modification, the differences between sampled and feed suspended sediment concentration were more consistent and the sampled to feed concentration ratio was accurate to within 10% for particle sizes up to 250 µm.

SAFL Baffle retrofit for suspended sediment removal in storm sewer sumps.

Standard sumps (manholes) provide a location for pipe junctions and maintenance access in stormwater drainage systems. Standard sumps can also remove sand and silt particles from stormwater, but have a high propensity for washout of the collected sediment. With appropriate maintenance these sumps may qualify as a stormwater best management practice (BMP) device for the removal of suspended sediment from stormwater runoff. To decrease the maintenance frequency and prevent standard sumps from becoming a source of suspended sediment under high flow conditions, a porous baffle, named the SAFL Baffle, has been designed and tested as a retrofit to the sump. Multiple configurations with varying percent open area and different angles of attack were evaluated in scale models. An optimum configuration was then constructed at the prototype scale and evaluated for both removal efficiency and washout. Results obtained with the retrofit indicate that with the right baffle dimensions and porosity, sediment washout from the sump at high flow rates can be almost eliminated, and removal efficiency can be significantly increased at low flow rates. Removal efficiency and washout functions have been developed for standard sumps retrofitted with the SAFL Baffle. The results of this research provide a new, versatile stormwater treatment device and implemented new washout and removal efficiency testing procedures that will improve research and development of stormwater treatment devices.