Optimal trap velocity in a dynamic holographic optical trap using a nematic liquid crystal spatial light modulator

A dynamic holographic optical trap uses a dynamic diffractive optical element such as a liquid crystal spatial light modulator to realize one or more optical traps with independent controls. Such holographic optical traps provide a number of flexibilities and conveniences useful in various applications. One key requirement for such a trap is the ability to move the trapped microscopic object from one point to the other with the optimal velocity. In this paper we develop a nematic liquid crystal spatial light modulator based holographic optical trap and experimentally investigate the optimal velocity feasible for trapped beads of different sizes, in such a trap. Our results show that the achievable velocity of the trapped bead is a function of size of the bead, step size, interval between two steps and power carried by the laser beam. We observe that the refresh rate of a nematic liquid crystal spatial light modulator is sufficient to achieve an optimal velocity approaching the theoretical limit in the respective holographic trap for beads with radius larger than the wavelength of light.

Plantar flexor muscles of kangaroo rats (D. deserti) shorten at a velocity to produce optimal power during jumping

During jumping by kangaroo rats, the musculotendon work contributions across all joints are not well understood. Namely, measures of external joint work do not provide information on the contributions from individual muscles or in-series elastic structures. In this study, we examined the functional roles of a major ankle extensor muscle, lateral gastrocnemius (LG), and of a major knee extensor muscle, vastus lateralis (VL), through in vivo sonomicrometry and electromyography techniques, during vertical jumping by kangaroo rats. Our data showed that both muscles increased shortening and activity with higher jumps. We found that knee angular velocity and VL muscle shortening velocity were coupled in time. In contrast, the ankle angular velocity and LG muscle shortening velocity were decoupled, and rapid joint extension near the end of the jump produced high power outputs at the ankle joint. Further, the decoupling of muscle and joint kinematics allowed the LG muscle to prolong the period of shortening velocity near optimal velocity (Vopt), which likely enabled the muscle to sustain maximal power generation. These observations were consistent with a LG tendon that is much more compliant than that of the VL.

Time-Optimal Velocity Tracking Control for Consensus Formation of Multiple Nonholonomic Mobile Robots

The problem of velocity tracking is considered essential in the consensus of multi-wheeled mobile robot systems to minimise the total operating time and enhance the system’s energy efficiency. This study presents a novel switched-system approach, consisting of bang-bang control and consensus formation algorithms, to address the problem of time-optimal velocity tracking of multiple wheeled mobile robots with nonholonomic constraints. This effort aims to achieve the desired velocity formation in the least time for any initial velocity conditions in a multiple mobile robot system. The main findings of this study are as follows: (i) by deriving the equation of motion along the specified path, the motor’s extremal conditions for a time-optimal trajectory are introduced; (ii) utilising a general consensus formation algorithm, the desired velocity formation is achieved; (iii) applying the Pontryagin Maximum Principle, the new switching formation matrix of weights is obtained. Using this new switching matrix of weights guarantees that at least one of the system’s motors, of either the followers or the leader, reaches its maximum or minimum value by using extremals, which enables the multi-robot system to reach the velocity formation in the least time. The proposed approach is verified in a theoretical analysis along with the numerical simulation process. The simulation results demonstrated that using the proposed switched system, the time-optimal consensus algorithm behaved very well in the networks with different numbers of robots and different topology conditions. The required time for the consensus formation is dramatically reduced, which is very promising. The findings of this work could be extended to and beneficial for any multi-wheeled mobile robot system.

A Method of Optimal Control for Class 8 Vehicle Platoons Over Hilly Terrain

This work develops and implements an NMPC control system to facilitate fuel-optimal platooning of Class 8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive Cruise Control (CACC), which allows multiple Class 8 vehicles to follow in close succession, can save between 3 and 8% in overall fuel consumption on flat terrain. However, on more challenging terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings, and, in some cases, an increase in fuel consumption relative to individual vehicle operation. This research explores the use of Nonlinear Model Predictive Control (NMPC) with predefined route grade profiles to allow platooning vehicles to generate an optimal velocity trajectory with respect to fuel consumption. In order to successfully implement the NMPC system, a model relating vehicle velocity to fuel consumption was generated and validated using experimental data. Additionally, the predefined route grade profiles were created by using the vehicle's GPS velocity over the desired terrain. The real-time NMPC system was then implemented on a two-truck platoon operating over challenging terrain, with a reference vehicle running individually. The results from NMPC platooning are compared against fuel results from a classical proportional-integral-derivative (PID) headway control method. This comparison yields the comparative fuel savings and energy efficiency benefit of NMPC system. In the final analysis, significant fuel savings of greater than 14 and 20% were seen for the lead and following vehicles relative to their respective traditional cruise control and platooning architectures.

Impact of interruption probability of the current optimal velocity on traffic stability for car-following model

Traffic interruption is one of the important factors resulting in traffic jam. Therefore, a new optimal velocity model is established involving the traffic interruption probability for self-expected velocity. Linear stable condition and mKdV equation are deduced with regard to the self-interruption probability of the current optimal velocity from linear stable analysis and nonlinear analysis, respectively. Moreover, numerical simulation reveals that the traffic self-interruption probability of the current optimal velocity can increase traffic stability, which certifies that the traffic self-interruption probability of the current optimal velocity plays important influences on traffic system.

Children’s vicarious ratings of social touch are tuned to the velocity but not the location of a caress

Affective sharing is a bottom-up process involving automatic processing of sensory inputs that facilitate vicarious experience of another’s emotional state. It is grounded directly in the prior experiences of the perceiver. In adults, vicarious ratings of affective touch match the known velocity tuning and hypothesised anatomical distribution of C-tactile afferents (CT), a subclass of C-fibre which respond preferentially to low force/velocity stroking touch, typically perceived as pleasant. Given the centrality of touch to early nurturing interactions, here we examined whether primary school aged children’s vicarious ratings of affective touch show the same anatomical and velocity specific patterns reported in adults. Forty-four children aged between 8 and 11 (mean age 9, 24 male) rated a sequence of video clips depicting one individual being touched by another on 5 different upper-body sites (palm, dorsal forearm, ventral forearm, upper-arm and back) at 3 different velocities (static, CT optimal, slow stroking and non-CT optimal, fast stroking). Immediately after viewing each clip, participants were asked to rate how pleasant they perceived the touch to be. While children rated the CT optimal velocity significantly higher than static or non-CT optimal touch, unlike adults their ratings did not vary across skin sites. This difference may reflect the fact children’s ratings are grounded in bottom-up affective resonance while adults also draw on top-down cognitive evaluation of the broader social context when rating the stimuli.

EffMoP: Efficient Motion Planning Based on Heuristic-Guided Motion Primitives Pruning and Path Optimization With Sparse-Banded Structure

To solve the autonomous navigation problem in complex environments, an efficient motion planning approach called EffMoP is presented in this paper. Considering the challenges from large-scale, partially unknown complex environments, a three-layer motion planning framework is elaborately designed, including global path planning, local path optimization, and time-optimal velocity planning. Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of the underlying optimization problem is fully exploited to efficiently solve the problem. We validate the safety, smoothness, flexibility, and efficiency of EffMoP in various complex simulation scenarios and challenging real-world tasks.

EffMoP: Efficient Motion Planning Based on Heuristic-Guided Motion Primitives Pruning and Path Optimization With Sparse-Banded Structure

To solve the autonomous navigation problem in complex environments, an efficient motion planning approach called EffMoP is presented in this paper. Considering the challenges from large-scale, partially unknown complex environments, a three-layer motion planning framework is elaborately designed, including global path planning, local path optimization, and time-optimal velocity planning. Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of the underlying optimization problem is fully exploited to efficiently solve the problem. We validate the safety, smoothness, flexibility, and efficiency of EffMoP in various complex simulation scenarios and challenging real-world tasks.

EffMoP: Efficient Motion Planning Based on Heuristic-Guided Motion Primitives Pruning and Path Optimization With Sparse-Banded Structure

To solve the autonomous navigation problem in complex environments, an efficient motion planning approach called EffMoP is presented in this paper. Considering the challenges from large-scale, partially unknown complex environments, a three-layer motion planning framework is elaborately designed, including global path planning, local path optimization, and time-optimal velocity planning. Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of the underlying optimization problem is fully exploited to efficiently solve the problem. We validate the safety, smoothness, flexibility, and efficiency of EffMoP in various complex simulation scenarios and challenging real-world tasks.