scholarly journals Dynamics and stability of running on rough terrains

2019 ◽  
Vol 6 (3) ◽  
pp. 181729 ◽  
Author(s):  
Nihav Dhawale ◽  
Shreyas Mandre ◽  
Madhusudhan Venkadesan
Keyword(s):  
Sensory Feedback ◽  
Dimensionless Parameter ◽  
Sagittal Plane ◽  
Sensory Information ◽  
Open Loop ◽  
Rough Terrain ◽  
Two Dimensional ◽  
Flat Surfaces ◽  
And Control ◽  
Flat Ground

Stability of running on rough terrain depends on the propagation of perturbations due to the ground. We consider stability within the sagittal plane and model the dynamics of running as a two-dimensional body with alternating aerial and stance phases. Stance is modelled as a passive, impulsive collision followed by an active, impulsive push-off that compensates for collisional losses. Such a runner has infinitely many strategies to maintain periodic gaits on flat ground. However, these strategies differ in how perturbations due to terrain unevenness are propagated. Instabilities manifest as tumbling (orientational instability) or failing to maintain a steady speed (translational instability). We find that open-loop strategies that avoid sensory feedback are sufficient to maintain stability on step-like terrains with piecewise flat surfaces that randomly vary in height. However, these open-loop runners lose orientational stability on rough terrains whose slope also varies randomly. The orientational instability is significantly mitigated by minimizing the tangential collision, which typically requires sensory information and anticipatory strategies such as leg retraction. By analysing the propagation of perturbations, we derive a single dimensionless parameter that governs stability. This parameter provides guidelines for the design and control of both biological and robotic runners.

scholarly journals Advantages of comparative studies in songbirds to understand the neural basis of sensorimotor integration

2017 ◽  
Vol 118 (2) ◽  
pp. 800-816 ◽  
Author(s):  
Karagh Murphy ◽  
Logan S. James ◽  
Jon T. Sakata ◽  
Jonathan F. Prather
Keyword(s):  
Nervous System ◽  
Sensory Feedback ◽  
Sensorimotor Integration ◽  
New Technologies ◽  
Sensory Information ◽  
Neural Basis ◽  
Communication Behaviors ◽  
Song Repertoire ◽  
Evolutionary Variation ◽  
And Control

Sensorimotor integration is the process through which the nervous system creates a link between motor commands and associated sensory feedback. This process allows for the acquisition and refinement of many behaviors, including learned communication behaviors such as speech and birdsong. Consequently, it is important to understand fundamental mechanisms of sensorimotor integration, and comparative analyses of this process can provide vital insight. Songbirds offer a powerful comparative model system to study how the nervous system links motor and sensory information for learning and control. This is because the acquisition, maintenance, and control of birdsong critically depend on sensory feedback. Furthermore, there is an incredible diversity of song organizations across songbird species, ranging from songs with simple, stereotyped sequences to songs with complex sequencing of vocal gestures, as well as a wide diversity of song repertoire sizes. Despite this diversity, the neural circuitry for song learning, control, and maintenance remains highly similar across species. Here, we highlight the utility of songbirds for the analysis of sensorimotor integration and the insights about mechanisms of sensorimotor integration gained by comparing different songbird species. Key conclusions from this comparative analysis are that variation in song sequence complexity seems to covary with the strength of feedback signals in sensorimotor circuits and that sensorimotor circuits contain distinct representations of elements in the vocal repertoire, possibly enabling evolutionary variation in repertoire sizes. We conclude our review by highlighting important areas of research that could benefit from increased comparative focus, with particular emphasis on the integration of new technologies.

scholarly journals Dynamic Stability of Open-Loop Hopping

2006 ◽  
Vol 129 (3) ◽  
pp. 275-284 ◽  
Author(s):  
Jorge G. Cham ◽  
Mark R. Cutkosky
Keyword(s):  
Sensory Feedback ◽  
Motor Pattern ◽  
Open Loop ◽  
Legged Robots ◽  
Open Loop System ◽  
System Parameters ◽  
Model Driven ◽  
The Stability ◽  
And Control ◽  
Hopping Model

Simulations and physical robots have shown that hopping and running are possible without sensory feedback. However, stable behavior is often limited to a certain range of the parameters of the open-loop system. Even the simplest of hopping systems can exhibit unstable behavior that results in unpredictable nonperiodic motion as system parameters are adjusted. This paper analyzes the stability of a simplified vertical hopping model driven by an open-loop, feedforward motor pattern. Periodic orbits of the resulting hybrid system are analyzed through a generalized formula for the system’s Poincare Map and Jacobian. The observed behavior is validated experimentally in a physical pneumatically actuated hopping machine. This approach leads to observations on the stability of this and similar systems, revealing inherent limitations of open-loop hopping and providing insights that can inform the design and control of dynamic legged robots capable of rapid and robust locomotion.

Design and Control of a Three Finger Hand Exoskeleton for Translation and Rotation of a Slender Object

2015 ◽  
Author(s):  
Shyam Sunder Nishad ◽  
Anupam Saxena ◽  
Ashish Dutta
Keyword(s):  
Position Control ◽  
Sagittal Plane ◽  
Search Algorithm ◽  
Experimental Tests ◽  
Dorsal Side ◽  
Open Loop ◽  
Video Capture ◽  
Out Of Plane ◽  
Serially Concatenated ◽  
And Control

A three-finger exoskeleton is designed and controlled to translate and or rotate a slender object held between the fingertips. Each finger exoskeleton comprises of three serially concatenated planar external four-bar linkages, all on one plane, except for the thumb exoskeleton, for which one linkage is out of plane. Linkages are constrained to be on the dorsal side (sagittal plane) of each finger. To design each linkage, when performing coordinated translation and rotation, trajectories of all phalanges of the index and middle fingers and the thumb are obtained through video capture and post-processing that involves coordinate transformation. Optimal kinematic synthesis for each linkage is then performed via the three accuracy point method coupled with a stochastic search algorithm. Post manufacturing, the exoskeleton is mounted on the dorsal side of the hand using Velcro bands. Fastening is accomplished on each phalanx, palm and forearm via a fixture designed to house all three exoskeletons. Nine micro-servo motors are employed for actuation. To perform coordinated translation and rotation tasks, trajectory following is accomplished using open loop position control, incorporating artificial neural network to convert known finger joint angles into the required driving link angles. Based on experimental tests conducted, the exoskeleton is found to be successful in reproducing the requisite finger motions involved in coordinated object manipulation.

Neuromuscular Control of Movement

2018 ◽  
Keyword(s):  
Nervous System ◽  
Sensory Information ◽  
Neuromuscular Control ◽  
Complex Environments ◽  
Locomotor Rhythm ◽  
Motor Responses ◽  
Reflex Pathways ◽  
Local Reflex ◽  
Local Circuits ◽  
And Control

The control of movement is essential for animals traversing complex environments and operating across a range of speeds and gaits. We consider how animals process sensory information and initiate motor responses, primarily focusing on simple motor responses that involve local reflex pathways of feedback and control, rather than the more complex, longer-term responses that require the broader integration of higher centers within the nervous system. We explore how local circuits facilitate decentralized coordination of locomotor rhythm and examine the fundamentals of sensory receptors located in the muscles, tendons, joints, and at the animal’s body surface. These sensors monitor the animal’s physical environment and the action of its muscles. The sensory information is then carried back to the animal’s nervous system by afferent neurons, providing feedback that is integrated at the level of the spinal cord of vertebrates and sensory-motor ganglia of invertebrates.

Effects of shoulder translation on lumbar moment for two dimensional modeling strategies during lifting

1998 ◽  
Vol 1 (3) ◽  
pp. 173-187
Author(s):  
Wayne J. Albert ◽  
Joan M. Stevenson ◽  
Geneviève A. Dumas ◽  
Roger W. Wheeler
Keyword(s):  
Sagittal Plane ◽  
Tracking System ◽  
Vertical Direction ◽  
Two Dimensional ◽  
Model Type ◽  
Trunk Acceleration ◽  
Analysis System ◽  
Trunk Orientation ◽  
Shoulder Position ◽  
Dynamic Link

The objectives of this study were to: 1) develop a dynamic 2D link segment model for lifting using the constraints of four sensors from an electromagnetic motion analysis system; 2) evaluate the magnitude of shoulder movement in the sagittal plane during lifting; and 3) investigate the effect of shoulder translation on trunk acceleration and lumbar moments calculated by the developed model and comparing it with two separate 2D dynamic link segment models. Six women and six men lifted loads of 2 kg, 7 kg, 12 kg and 2 kg, 12 kg, 22 kg respectively, under stoop, squat and freestyle conditions. Trunk orientation and position, as well as shoulder position were monitored during all lifts using the Polhemus FASTRAK\trdmk. Results indicated that average range of motion was 0.05 ± 0.02 m in the horizontal direction and 0.03 ± 0.02 m in the vertical direction. Shoulder position relative to T1 was located 0.07 ± 0.02 m anteriorly, and 0.02 ± 0.04 m superiorly (0.06 and 0.00 m for males and 0.08 and 0.04 m for females, respectively). To estimate the effect of shoulder motion on trunk acceleration and L5/S1 moments, three two-dimensional dynamic link segment models were developed within the constraints of the electromagnetic tracking system and compared. Trunk segment endpoints were defined as L5/S1 and either T1 or shoulder depending on model type. For trunk accelerations, average differences between models were greater than 40 deg/s² in 70.4% trunk accelerations did not translate into significantly different moment calculations between models. Average peak dynamic L5/S1 moment differences between models were smaller than 4 Nm for all lifting conditions which failed to be statistically significant (p>0.05). The model type did not have a statistically significant effect on peak L5/S1 moments. Therefore, despite important shoulder joint translations, peak L5/S1 moments were not significantly affected.

MYMOSA: Towards the Simulation of Realistic Motorcycle Manoeuvres by Coupling Multibody and Control Techniques

2008 ◽  
Author(s):  
David Moreno Giner ◽  
Claudio Brenna ◽  
Ioannis Symeonidis ◽  
Gueven Kavadarlic
Keyword(s):  
Rear Wheel ◽  
Open Loop ◽  
Dynamics Simulation ◽  
Engine Torque ◽  
Multibody Model ◽  
Physiological Limits ◽  
Research Activities ◽  
Analysis Technique ◽  
First Results ◽  
And Control

Multibody dynamics simulation technology can provide a great help to understand and analyze motorcycle dynamics. In fact, its application in this field has grown very fast in the last years. However, apart from the mathematical model of the vehicle, a virtual rider is essential in order to properly simulate a motorcycle. This is due to the unstable nature of two-wheeled vehicles, which makes them very difficult to simulate by using open-loop maneuvers. The problem of developing a virtual rider for motorcycles has already been covered in literature but most of the proposed control algorithms achieved their purpose without considering the physiological limits of the rider. The objective of the research activities presented here are the preliminary development of a realistic virtual rider based on an experimental campaign and its subsequent simulation together with a detailed multibody model of a motorcycle. Special emphasis was put on making the rider model as simple as possible to facilitate the posterior design of the controller. Real rider movements were measured under laboratory conditions by means of the Motion Analysis technique. Several volunteers with different riding experiences, gender and anthropometry were involved in the experiments in order to provide a valid dataset for the analysis. For the present research, the virtual rider controls the direction of the motorcycle by means of both a torque on the handlebars and the movement of his body. The upper part of the rider’s body was modeled as an inverted pendulum. With regard to the longitudinal dynamics, the motorcycle is controlled by means of the brake torques and by the engine torque, which is transmitted to the rear wheel by means of a simplified model of the chain. First results of the developed virtual rider are presented at the end of this paper.

Comparative studies of the set up of two-dimensional pneumatic arm systems by muscle and rotational actuators

2007 ◽  
Vol 221 (5) ◽  
pp. 743-748 ◽  
Author(s):  
Y-T Wang ◽  
R-H Wong ◽  
J-T Lu
Keyword(s):  
Control Systems ◽  
Fuzzy Controller ◽  
Control Algorithms ◽  
Two Dimensional ◽  
Pneumatic Control ◽  
Learning Mechanism ◽  
Set Up ◽  
And Control ◽  
Self Learning ◽  
System Characteristics

As opposed to traditional pneumatic linear actuators, muscle and rotational actuators are newly developed actuators in rotational and specified applications. In the current paper, these actuators are used to set up two-dimensional pneumatic arms, which are used mainly to simulate the excavator's motion. Fuzzy control algorithms are typically applied in pneumatic control systems owing to their non-linearities and ill-defined mathematical model. The self-organizing fuzzy controller, which includes a self-learning mechanism to modify fuzzy rules, is applied in these two-dimensional pneumatic arm control systems. Via a variety of trajectory tracking experiments, the present paper provides comparisons of system characteristics and control performances.

scholarly journals The emulation theory of representation: Motor control, imagery, and perception

2004 ◽  
Vol 27 (3) ◽  
pp. 377-396 ◽  
Author(s):  
Rick Grush
Keyword(s):  
Motor Control ◽  
Sensory Feedback ◽  
Sensory Input ◽  
Neural Circuits ◽  
Sensory Information ◽  
The Body ◽  
Feedback Delay ◽  
Run Off ◽  
Effects Of Feedback ◽  
The Brain

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.

Open-Loop Control Co-Design of Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

2021 ◽  
Author(s):  
Athul K. Sundarrajan ◽  
Yong Hoon Lee ◽  
James T. Allison ◽  
Daniel R. Herber
Keyword(s):  
Wind Turbines ◽  
Open Loop ◽  
Offshore Wind ◽  
Linear Parameter ◽  
Design Decisions ◽  
Linear Parameter Varying ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Parameter Varying ◽  
And Control

Abstract This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines (FOWTs) in an integrated manner using linear parameter-varying models. Multiple linearized models derived from high-fidelity software are used to model the system in different operating regions characterized by the incoming wind speed. The combined model is then used to generate open-loop optimal control trajectories as part of a nested control co-design strategy that explores the system’s stability and power production in the context of crucial plant and control design decisions. A cost model is developed for the FOWT system, and the effect of plant decisions and subsequent power and stability response of the FOWT is quantified in terms of the levelized cost of energy (LCOE) for that system. The results show that the stability constraints and the plant design decisions affect the turbine’s power and, subsequently, LCOE of the system. The results indicate that a lighter plant in terms of mass can produce the same power for a lower LCOE while still satisfying the constraints.

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