The Limb Kinetics of Goat Walking on the Slope with Different Angles

The study aimed to assess the gait adjustment techniques of limbs on different slopes and investigate the relationship between forelimb and hindlimb kinetics and the center of mass (COM) during the uphill movement of a specific Boer goat using a pressure-sensitive walkway (PSW). During the uphill and downhill movements at a comfortable walking speed, we measured the ground reaction force (GRF) of the forelimbs and hindlimbs on the slope, the change in the included angle of the propulsive force direction of the forelimbs and hindlimbs, and the impulse relationship between GRF and propulsive force. According to the study, since the forelimbs of the goat were nearer the COM, they were primarily adjusted during the movement on the slope. By lowering the initial included angle of the propulsive force and the angle variation range, the forelimbs and hindlimbs could walk steadily. The forelimbs and hindlimbs exhibited completely different adjustment strategies during uphill and downhill movements. In particular, the forelimbs performed braking and the hindlimbs performed driving. In addition, we discovered that the goat altered its adjustment strategy when climbing the steep slope. All findings of this study indicate the need to understand the gait adjustment mode of the Boer goat during movement on the slope to thoroughly comprehend the driving strategy of quadrupeds with the ability to walk on specialized terrains.

Online sensorimotor learning and adaptation for inverse dynamics control

We propose a micro-data (< 10 trials) sensorimotor learning and adaptation (SEED) model for human-like arm inverse dynamics control. The SEED model consists of a feedforward Gaussian motor primitive (GATE) neural network and an adaptive feedback impedance (AIM) mechanism. Sensorimotor weights over trials are learned in the GATE network, while the AIM mechanism is used to online tune impedance gains in a trial. The model was validated by periodic and non-periodic tracking tasks on a two-joint robot arm. As a result, the proposed model enables the arm to stably learn the tasks within 10 trials, compared to thousands of trials required by state-of-art deep learning. This model facilitates the exploration of unknown arm dynamics, in which the elbow joint requires much less active control compared to the shoulder. This control goes below 3% of the overall effort. This finding complies with a proximal-distal control gradient in human arm control. Taken together, the proposed SEED model paves a way for implementing data-efficient sensorimotor learning and adaptation of human-like arm movement.

From cockroaches to tanks: The same power-mass-speed relation describes both biological and artificial ground-mobile systems

This paper explores whether artificial ground-mobile systems exhibit a consistent regularity of relation among mass, power, and speed, similar to that which exists for biological organisms. To this end, we investigate an empirical allometric formula proposed in the 1980s for estimating the mechanical power expended by an organism of a given mass to move at a given speed, applicable over several orders of magnitude of mass, for a broad range of species, to determine if a comparable regularity applies to a range of vehicles. We show empirically that not only does a similar regularity apply to a wide variety of mobile systems; moreover, the formula is essentially the same, describing organisms and systems ranging from a roach (1 g) to a battle tank (35,000 kg). We also show that for very heavy vehicles (35,000–100,000,000 kg), the formula takes a qualitatively different form. These findings point to a fundamental similarity between biological and artificial locomotion that transcends great differences in morphology, mechanisms, materials, and behaviors. To illustrate the utility of this allometric relation, we investigate the significant extent to which ground robotic systems exhibit a higher cost of transport than either organisms or conventional vehicles, and discuss ways to overcome inefficiencies.

An extension to the collisional model of the energetic cost of support qualitatively explains trotting and the trot-canter transition

The majority of terrestrial mammals adopt distinct, discrete gaits across their speed range. Though there is evidence that walk, trot and gallop may be selected at speeds consistent with minimizing metabolic cost (Hoyt and Taylor, 1981, Nature, 291, 239-240), the mechanical causes underlying these costs and their changes with speed are not well understood. In particular, the paired, near-simultaneous contacts of the trot is puzzling as it appears to demand a high mechanical work that could easily be avoided with distributed contacts, as with a "running walk" gait or "tolt." Here, a simple condition is derived-a ratio including the pitch moment of inertia and back length-for which trotting is energetically advantageous because it avoids the energetic consequences of pitching. Pitching could also be avoided if the impulses from the legs were orientated through the center of mass. A range of idealized gaits is considered that achieve this zero-pitch condition, and work minimization predicts a transition from trot to canter at intermediate speeds. This can be understood from the geometric principles of achieving a "pseudoelastic" collision with each impulse (Ruina et al., 2005, J Theoretical Biol, 14, 170-192). However, at high speeds, a transition back to trot is predicted that is not observed in nature.

Collisional mechanics of the diagonal gaits of horses over a range of speeds

One of the goals of the neuromotor control system is to minimize the cost of locomotion by reducing mechanical energy losses. Collisional mechanics, which studies the redirection of the downwards motion of the center of mass (COM) by ground reaction forces (GRF) generated by the limbs, represents an important source of energy loss. The primary objective of this study was to compare collisional mechanics and the associated mechanical energy losses in horses performing diagonally-synchronized gaits over a range of speeds. It is to be expected that collisional energy losses will be high when the COM velocity vector is closely aligned with the GRF vector. This condition is achieved in piaffe, an artificial gait performed in dressage competitions that has a diagonal limb coordination pattern similar to trot but performed with little or no forward velocity. Therefore, we hypothesized that collisional energy losses would be higher in piaffe than in trot. Synchronized kinematic and GRF data were collected from three highly-trained horses performing piaffe, passage and trot at a range of speeds. Derived variables were vertical excursion and velocity of the trunk COM, fore and hind limb compression expressed as percentage reduction of standing limb lengths, range of limb pro-retraction, GRF vector magnitude and vector angle, collision angle (Φ), and mechanical cost of motion (CoMot_mech). Linear regression was used to investigate the relationship between CoMot_mech and speed for each gait. Partial correlation was used to seek relationships between COM excursion and limb mechanics for each gait. Piaffe, passage and trot were clearly separated on the basis of speed. In all gaits the trunk was high at contact and lift off and descended to its lowest point in midstance following the pattern typical of spring mass mechanics. Mechanical cost was significantly (p < .05) and inversely related to speed in trot and piaffe with the value increasing steeply as speed approached zero due to a near vertical orientation of both the COM velocity vector and the GRF vector. Limb compression during stance was significantly (p < .05) linked to trunk COM vertical excursion in all gaits, with a stronger relationship in the forelimb. Hindlimb compression was, however, large in piaffe where the force magnitudes are notably smaller. The study illustrates the potential value of studying artificial gaits to provide data encompassing the entire range of locomotor capabilities. The results supported the experimental hypothesis by showing a threefold increase in collisional energy losses in piaffe compared with trot. In all gaits, dissociation between diagonal limb contacts and lift offs was thought to be an important strategy in reducing in collisional losses. Piaffe, the most costly gait, has similar characteristics to hopping on the spot. It appears that greater hindlimb compliance and a lower step frequency are important energy conservation strategies for piaffe.

Development of an 8DOF quadruped robot and implementation of Inverse Kinematics using Denavit-Hartenberg convention

Quadruped robots can mimic animal walking gait and they have certain advantages like walking on terrain and extremely rough surfaces. Obstacles can impede the movement of wheeled vehicles, where a quadruped can adapt to avoid obstacles by adjusting its height. A quadruped robot is designed and developed for in this paper, which could be controlled by the Android operating system. The Inverse Kinematics Solutions are derived for the developed structure using Denavit-Hartenberg convention and using those solutions the movements are simulated using a custom-made 3D software. An Android application is developed, which is able to control the robot using Bluetooth. The robot currently has following six different movements: front, back, left, right walking, clockwise and anti-clockwise rotation. The robot uses the ultrasound sensor to detect any obstacle closer than 300 cm (maximum) and if an impediment appears, the robot will automatically move parallel to the obstacle until it is avoided. Currently, it can move at a speed of 15.5 cm/s (approximately). To complete a full rotation of 360°, it takes 6 seconds. It can be used to develop and implement any autonomous path-planning algorithm.

Timing of head movements is consistent with energy minimization in walking ungulates

Many ungulates show a conspicuous nodding motion of the head when walking. Until now, the functional significance of this behaviour remained unclear. Combining in vivo kinematics of quadrupedal mammals with a computer model, we show that the timing of vertical displacements of the head and neck is consistent with minimizing energy expenditure for carrying these body parts in an inverted pendulum walking gait. Varying the timing of head movements in the model resulted in increased metabolic cost estimate for carrying the head and neck of up to 63%. Oscillations of the head-neck unit result in weight force oscillations transmitted to the forelimbs. Advantageous timing increases the load in single support phases, in which redirecting the trajectory of the centre of mass (COM) is thought to be energetically inexpensive. During double support, in which-according to collision mechanics-directional changes of the impulse of the COM are expensive, the observed timing decreases the load. Because the head and neck comprise approximately 10% of body mass, the effect shown here should also affect the animals' overall energy expenditure. This mechanism, working analogously in high-tech backpacks for energy-saving load carriage, is widespread in ungulates, and provides insight into how animals economize locomotion.

Adaptive and Energy Efficient Walking in a Hexapod Robot Under Neuromechanical Control and Sensorimotor Learning

The control of multilegged animal walking is a neuromechanical process, and to achieve this in an adaptive and energy efficient way is a difficult and challenging problem. This is due to the fact that this process needs in real time: 1) to coordinate very many degrees of freedom of jointed legs; 2) to generate the proper leg stiffness (i.e., compliance); and 3) to determine joint angles that give rise to particular positions at the endpoints of the legs. To tackle this problem for a robotic application, here we present a neuromechanical controller coupled with sensorimotor learning. The controller consists of a modular neural network for coordinating 18 joints and several virtual agonist-antagonist muscle mechanisms (VAAMs) for variable compliant joint motions. In addition, sensorimotor learning, including forward models and dual-rate learning processes, is introduced for predicting foot force feedback and for online tuning the VAAMs' stiffness parameters. The control and learning mechanisms enable the hexapod robot advanced mobility sensor driven-walking device (AMOS) to achieve variable compliant walking that accommodates different gaits and surfaces. As a consequence, AMOS can perform more energy efficient walking, compared to other small legged robots. In addition, this paper also shows that the tight combination of neural control with tunable muscle-like functions, guided by sensory feedback and coupled with sensorimotor learning, is a way forward to better understand and solve adaptive coordination problems in multilegged locomotion.

A starfish robot based on soft and smart modular structure (SMS) actuated by SMA wires

This paper describes the design, fabrication and locomotion of a starfish robot whose locomotion principle is derived from a starfish. The starfish robot has a number of tentacles or arms extending from its central body in the form of a disk, like the topology of a real starfish. The arm, which is a soft and composite structure (which we call the smart modular structure (SMS)) generating a planar reciprocal motion with a high speed of response upon the actuation provided by the shape memory alloy (SMA) wires, is fabricated from soft and smart materials. Based on the variation in the resistance of the SMA wires during their heating, an adaptive regulation (AR) heating strategy is proposed to (i) avoid overheating of the SMA wires, (ii) provide bending range control and (iii) achieve a high speed of response favorable to successfully propelling the starfish robot. Using a finite-segment method, a thermal dynamic model of the SMS is established to describe its thermal behavior under the AR and a constant heating strategy. A starfish robot with five SMS tentacles was tested with different control parameters to optimize its locomotion speed. As demonstrated in the accompanying video file, the robot successfully propelled in semi-submerged and underwater environments show its locomotion ability in the multi-media, like a real starfish. The propulsion speed of the starfish robot is at least an order of magnitude higher than that of those reported in the literature-thanks to the SMS controlled with the AR strategy.