The three-dimensional locomotor dynamics of African (Loxodonta africana) and Asian (Elephas maximus) elephants reveal a smooth gait transition at moderate speed

We examined whether elephants shift to using bouncing (i.e. running) mechanics at any speed. To do this, we measured the three-dimensional centre of mass (CM) motions and torso rotations of African and Asian elephants using a novel multisensor method. Hundreds of continuous stride cycles were recorded in the field. African and Asian elephants moved very similarly. Near the mechanically and metabolically optimal speed (a Froude number (Fr) of 0.09), an inverted pendulum mechanism predominated. With increasing speed, the locomotor dynamics quickly but continuously became less like vaulting and more like bouncing. Our mechanical energy analysis of the CM suggests that at a surprisingly slow speed (approx. 2.2 m s(-1), Fr 0.25), the hindlimbs exhibited bouncing, not vaulting, mechanics during weight support. We infer that a gait transition happens at this relatively slow speed: elephants begin using their compliant hindlimbs like pogo sticks to some extent to drive the body, bouncing over their relatively stiff, vaulting forelimbs. Hence, they are not as rigid limbed as typically characterized for graviportal animals, and use regular walking as well as at least one form of running gait.     

未知不平整地面上的双足步行稳定控制

 针对未知的不平整地面环境,提出了双足机器人稳定步行控制算法,该算法由步态规划和传感器反馈控制两部分组成.采用被动倒立摆模型设计双足机器人的步态,使得双足机器人能够自然、节能的稳定行走.实时反馈控制用来适应地面环境的凹凸不平以及处理外部环境的扰动.控制器包括上身姿态控制、期望ZMP控制以及非线性落地控制三部分.双足机器人机构柔性的存在对机器人稳定性以及控制效果造成很坏的影响,甚至使反馈控制造成负面的效果,因此柔性的影响也被考虑到步行控制器的设计当中.利用双足机器人不平地面上的步行实验验证所提出步行控制算法的有效性.     

Footholds optimization for legged robots walking on complex terrain

This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains. The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles, and to improve its stability and safety when walking on complex terrain. By relying on the depth camera installed on the robot and obtaining the terrain heightmap, the algorithm converts the discrete grid heightmap into a continuous costmap. Then, it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion. Compared with most existing footholds selection algorithms that rely on discrete enumeration search, as far as we know, the proposed algorithm is the first to use a continuous optimization method. We successfully implemented the algorithm on a hexapod robot, and verified its feasibility in a walking experiment on a complex terrain.     

仿生双足水上行走机器人优化设计及控制方法

研究一种新型双足水上行走机器人推进机构及控制方法。借鉴蛇怪蜥蜴双足水上行走功能,分析双足机器人水上行走动力学机理;结合平面四杆机构运动和坐标转换公式,分析Watt-I型机构运动方程,用以模拟蛇怪蜥蜴的脚掌轨迹,设计双足水上行走机器人推进机构,建立机器人的虚拟样机模型并进行机构优化设计;设计机器人的中枢模式发生器(Central pattern generator,CPG)控制器和模糊控制器并进行参数分析,提出双足水上行走机器人的CPG-模糊控制方法,完成机器人控制系统的搭建,进行仿真验证;制作出双足水上行走样机,进行双足机器人水上行走试验,测得推进机构的作用力曲线;在平衡装置不工作和工作情况下分别测量机器人水上行走过程中的实时偏角,并进行比较。试验结果表明推进机构及控制方法满足双足机器人水上行走要求。     

A novel robotic leg design with hybrid dynamics

A new leg mechanism is designed to achieve optimal behaviour in both the stance and swing phases. The leg is designed such that its dynamics and kinematics optimally mimic those of simpler mechanisms, namely the spring-loaded inverted pendulum (SLIP) and the double pendulum, for the stance and swing phase, respectively. Controllers based on the simpler mechanisms can thus be used, resulting in an effective control strategy that is simple and transparent.     

Dissociation of conditioned locomotion and Fos induction in response to stimuli formerly paired with cocaine.

A discrete stimulus (flashing light) was paired with cocaine (20 mg/kg) to induce conditioned locomotion. To identify brain regions activated during this response, Fos was measured with immunohistochemistry. Although paired subjects displayed robust conditioned locomotion, Fos was not increased in any limbic brain regions analyzed. In contrast, pairing of cocaine with generalized contextual cues (whole room) produced conditioned locomotion and Fos activation in the prelimbic portion of prefrontal cortex and the nucleus accumbens core. These results suggest that the pattern of neuronal activation during cocaine-conditioned activity differs depending on whether a discrete or contextual stimulus is used as a conditioned stimulus. The possibility that expectancy and frustrative nonreward contribute to Fos expression in rats conditioned to contextual cues is discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Design and control of compliant tensegrity robots through simulation and hardware validation

To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center, Moffett Field, CA, USA, has developed and validated two software environments for the analysis, simulation and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity (‘tensile–integrity’) structures have unique physical properties that make them ideal for interaction with uncertain environments. Yet, these characteristics make design and control of bioinspired tensegrity robots extremely challenging. This work presents the progress our tools have made in tackling the design and control challenges of spherical tensegrity structures. We focus on this shape since it lends itself to rolling locomotion. The results of our analyses include multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures that have been tested in simulation. A hardware prototype of a spherical six-bar tensegrity, the Reservoir Compliant Tensegrity Robot, is used to empirically validate the accuracy of simulation.     

Reflex-oscillations in evolved single leg neurocontrollers for walking machines

As a prerequisite for developing neural control for walking machines that are able to autonomously navigate through rough terrain, artificial structure evolution is used to generate various single leg controllers. The structure and dynamical properties of the evolved (recurrent) neural networks are then analysed to identify elementary mechanisms of sensor-driven walking behaviour. Based on the biological understanding that legged locomotion implies a highly decentralised and modular control, neuromodules for single, morphological distinct legs of a hexapod walking machine were developed by using a physical simulation. Each of the legs has three degrees of freedom (DOF). The presented results demonstrate how extremely small reflex-oscillators, which inherently rely on the sensorimotor loop and e.g. hysteresis effects, generate effective locomotion. Varying the fitness function by randomly changing the environmental conditions during evolution, neural control mechanisms are identified which allow for robust and adaptive locomotion. Relations to biological findings are discussed.