Template Based Control of Hexapedal Running

In this paper, we introduce a hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body lengths per second with reliable stability and rapid maneuverability. We use a low dimensional passively compliant biped as a template -- a control target for the alternating tripod gait of the physical machine. We impose upon the physical machine an approrimate inverse dynamics within-stride controller designed to force the true high dimensional system dynamics down onto the lower dimensional subspace corresponding to the template. Numerical simulations suggest the presence of asymptotically stable mnning gaits with large basins of attraction. Moreover, this controller improves substantially the maneuverability and dynamic range of RHex\u27s running behaviors relative to the initial prototype open-loop algorithms

A robust sagittal plane hexapedal running model with serial elastic actuation and simple periodic feedforward control

In this article we present a sagittal plane, sprawled posture hexapedal running model with distributed body inertia, massless legs and serial elastic actuation at the hips as well as along the telescoping legs. We show by simulation that simple, periodic, feedforward controlled actuation is sufficient to obtain steady period 1 running gaits at twice the actuation frequency. We observe a nearly linear relation of average running speed and actuation frequency. The ground reaction profiles of the legs show leg specialization as observed in running insects. Interleg phasing has a strong influence on the foot fall sequence and thus the overall body dynamics. While the single leg ground reaction force profiles show little dependency on interleg actuation phase the total reaction force does. Thus, depending on the interleg actuation phase body motions without flight phase are observed as well as body motions and total ground reaction forces that show similarities to those obtained for the spring loaded inverted pendulum model. Further, we show that including leg damping and a ground friction model the periodic orbits have a large region of attraction with respect to the initial conditions. Additionally, the model quickly rejects step up and step down disturbances as well as force impulses. Finally, we briefly discuss the energetics of the hexapedal running model

Rapid inversion: running animals and robots swing like a pendulum under ledges.

Escaping from predators often demands that animals rapidly negotiate complex environments. The smallest animals attain relatively fast speeds with high frequency leg cycling, wing flapping or body undulations, but absolute speeds are slow compared to larger animals. Instead, small animals benefit from the advantages of enhanced maneuverability in part due to scaling. Here, we report a novel behavior in small, legged runners that may facilitate their escape by disappearance from predators. We video recorded cockroaches and geckos rapidly running up an incline toward a ledge, digitized their motion and created a simple model to generalize the behavior. Both species ran rapidly at 12-15 body lengths-per-second toward the ledge without braking, dove off the ledge, attached their feet by claws like a grappling hook, and used a pendulum-like motion that can exceed one meter-per-second to swing around to an inverted position under the ledge, out of sight. We discovered geckos in Southeast Asia can execute this escape behavior in the field. Quantification of these acrobatic behaviors provides biological inspiration toward the design of small, highly mobile search-and-rescue robots that can assist us during natural and human-made disasters. We report the first steps toward this new capability in a small, hexapedal robot

Heterogeneous Leg Stiffness and Roll in Dynamic Running

Legged robots are by nature strongly non-linear, high-dimensional systems whose full complexity permits neither tractable mathematical analysis nor comprehensive numerical study. In consequence, a growing body of literature interrogates simplified “template” [1], [2] models—to date almost exclusively confined to sagittal- or horizontal-plane motion—with the aim of gaining insight into the design or control of the far messier reality. In this paper we introduce a simple bounding-in-place (“BIP”) model as a candidate frontal plane template for straight-ahead level ground running and explore its use in formulating hypotheses about whether and why rolling motion is important in legged locomotion. Numerical study of left-right compliance asymmetry in the BIP model suggests that compliance ratios yielding lowest steady state roll suffer far longer disturbance recovery transients than those promoting greater steady state roll. We offer preliminary experimental data obtained from video motion capture data of the frontal plane disturbance recovery patterns of a RHex-like hexapod suggesting a correspondence to the conclusions of the numerical study. Fig. 1. EduBot [19], a RHex-like [20] hexapedal robot. Jonathan Clark was supported by the IC Postdoctoral Fellow Program under grant number HM158204-1-2030. Samuel Burden was supported by the SUNFEST REU program at the University of Pennsylvania. This work was also partially supported by the NSF FIBR grant #0425878. For more information: Kod*La

Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics

Properly designing a system to exhibit favorable natural dynamics can greatly simplify designing or learning the control policy. However, it is still unclear what constitutes favorable natural dynamics and how to quantify its effect. Most studies of simple walking and running models have focused on the basins of attraction of passive limit-cycles and the notion of self-stability. We instead emphasize the importance of stepping beyond basins of attraction. We show an approach based on viability theory to quantify robust sets in state-action space. These sets are valid for the family of all robust control policies, which allows us to quantify the robustness inherent to the natural dynamics before designing the control policy or specifying a control objective. We illustrate our formulation using spring-mass models, simple low dimensional models of running systems. We then show an example application by optimizing robustness of a simulated planar monoped, using a gradient-free optimization scheme. Both case studies result in a nonlinear effective stiffness providing more robustness.Comment: 15 pages. This work has been accepted to IEEE Transactions on Robotics (2019

Automated Gait Adaptation for Legged Robots

Gait parameter adaptation on a physical robot is an error-prone, tedious and time-consuming process. In this paper we present a system for gait adaptation in our RHex series of hexapedal robots that renders this arduous process nearly autonomous. The robot adapts its gait parameters by recourse to a modified version of Nelder-Mead descent while managing its self-experiments and measuring the outcome by visual servoing within a partially engineered environment. The resulting performance gains extend considerably beyond what we have managed with hand tuning. For example, the hest hand tuned alternating tripod gaits never exceeded 0.8 m/s nor achieved specific resistance helow 2.0. In contrast, Nelder-Mead based tuning has yielded alternating tripod gaits at 2.7 m/s (well over 5 body lengths per second) and reduced specific resistance to 0.6 while requiring little human intervention at low and moderate speeds. Comparable gains have been achieved on the much larger ruggedized version of this machine