Back Flips with a Hexapedal Robot

We report on the design and analysis of a controller which can achieve dynamical self-righting of our hexapedal robot, RHex. We present an empirically developed control procedure which works reasonably well on indoor surfaces, using a hybrid energy pumping strategy to overcome torque limitations of its actuators. Subsequent modeling and analysis yields a new controller with a much wider domain of success as well as a preliminary understanding of the necessary hybrid control strategy. Simulation results demonstrate the superiority of the improved control strategy to the first generation empirically designed controller

Multi-point Contact Models for Dynamic Self-Righting of a Hexapod Robot

In this paper, we report on the design of a model-based controller that can achieve dynamical self-righting of a hexapod robot. Extending on our earlier work in this domain, we introduce a tractable multi-point contact model with Coulomb friction. We contrast the singularities inherent to the new model with other available methods and show that for our specific application, it yields dynamics which are well-defined. We then present a feedback controller that achieves “maximal” performance under morphological and actuation constraints, while ensuring the validity of the model by staying away from singularities. Finally, through systematic experiments, we demonstrate that our controller is capable of robust flipping behavior. For more information: Kod*La

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

Model-Based Dynamic Self-Righting Maneuvers for a Hexapedal Robot

We report on the design and analysis of a controller that can achieve dynamical self-righting of our hexapedal robot, RHex. Motivated by the initial success of an empirically tuned controller, we present a feedback controller based on a saggital plane model of the robot. We also extend this controller to develop a hybrid pumping strategy that overcomes actuator torque limitations, resulting in robust flipping behavior over a wide range of surfaces. We present simulations and experiments to validate the model and characterize the performance of the new controller

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover mothership. Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a local GPS) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed

Locomotion of Low-DoF Multi-legged Robots

Multi-legged robots inspired by insects and other arthropods have unique advantages when compared with bipedal and quadrupedal robots. Their sprawled posture provides stability, and allows them to utilize low-DoF legs which are easier to build and control. With low-DoF legs and multiple contacts with the environment, low-DoF multi-legged robots are usually over constrained if no slipping is allowed. This makes them intrinsically different from the classic bipedal and quadrupedal robots which have high-DoF legs and fewer contacts with the environment. Here we study the unique characteristics of low-DoF multi-legged robots, in terms of design, mobility and modeling. One key observation we prove is that 1-DoF multi-legged robots must slip to be able to steer in the plane. Slipping with multiple contacts makes it difficult to model these robots and their locomotion. Therefore, instead of relying on models, our primary strategy has been careful experimental study. We designed and built our own customized robots which are easily reconfigurable to accommodate a variety of research requirements. In this dissertation we present two robot platforms, BigAnt and Multipod, which demonstrate our design and fabrication methods for low-cost rapidly fabricated modular robotic platforms. BigAnt is a hexapedal robot with 1-DoF legs, whose chassis is constructed from foam board and fiber tape, and costs less than 20 USD in total; Multipod is a highly modular multi-legged robot that can be easily assembled to have different numbers of 2-DoF legs (4 to 12 legs discussed here). We conducted a detailed analysis of steering, including proposing a formal definition of steering gaits grounded in geometric mechanics, and demonstrated the intrinsic difference between legged steering and wheeled steering. We designed gaits for walking, steering, undulating, stair climbing, turning in place, and more, and experimentally tested all these gaits on our robot platforms with detailed motion tracking. Through the theoretical analyses and the experimental tests, we proved that allowing slipping is beneficial for improving the steering in our robots. Where conventional modeling strategies struggle due to multi-contact slipping, we made a significant scientific discovery: that multi-legged locomotion with slipping is often geometric in the sense known from the study of low Reynolds number swimmers and non-holonomic wheeled snake robots which have continuous contact with the environment. We noted that motion can be geometric ``on average'', i.e. stride to stride, and can be truly instantaneously geometric. For each of these we developed a data-driven modeling approach that allowed us to analyze the degree to which a motion is geometric, and applied the analysis to BigAnt and Multipod. These models can also be used for robot motion planning. To explore the mechanism behind the geometric motion characteristics of these robots, we proposed a spring supported multi-legged model. We tested the simulation based on this model against experimental data for all the systems we studied: BigAnt, Multipod, Mechapod (a variant of 6-legged Multipod) and cockroaches. The model prediction results captures many key features of system velocity profiles, but still showed some systematic errors (which can be alleviated ad-hoc). Our work shows the promise of low-DoF multi-legged robots as a class of robotic platforms that are easy to build and simulate, and have many of the mobility advantages of legged systems without the difficulties in stability and control that appear in robots with four or fewer legs.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169985/1/danzhaoy_1.pd

Bio-inspired Antennal Tactile Sensing

Vision dominates perception research in robotics and biology, but for many animals, it is not the dominant sensory system. Indeed, arthropods often rely on sensory cues sampled via a pair of passive head-mounted antennae to achieve navigation and control. These mechanosensory structures support multimodal receptors—tactile, hygrometric, thermal, olfactory—enabling a wide range of sensorimotor behaviors. One model biological system, Periplaneta americana cockroach, performs a remarkably robust escape behavior by using its long, slender, flexible antennae to facilitate rapid closed-loop course control. The antenna is a passive, hyper-redundant kinematic linkage that acts as a distributed tactile sensory structure to mediate mechanical interactions with the environment at very high rates. This thesis demonstrates that the antennal mechanics are tuned to enable high-speed, high-bandwidth locomotor control even in total darkness. Despite the extraordinary success of antennal sensing in nature, there are few effective bio-inspired antennae. To incorporate similar antennal sensing capability in agile mobile robots, I developed a tunable bio-inspired modular robotic research antenna and experimentation platform. I also synthesized numerical models to approximate antenna mechanics under relevant boundary conditions, which I verified against my physical model. Both numerical simulations and physical experiments were conducted to isolate fundamental parameters that underly the stability and performance I observed in the biological model. Using a combination of numerical and robotic experiments, in concert with biological experiments conducted by my collaborators, I discovered that several behaviorally relevant characteristics of an antennae are predominantly governed by a combination of (1) the stiffness profile of the antenna and (2) the interaction of hairlike mechano-structures along the length of the antenna. I found that the “right” combination of these features improves the postural stability and the steady state spatial acuity of tactile interaction with the environment. Specifically, antennae with an exponentially decreasing stiffness profile accompanied by distally pointing anisotropic mechano-hairs are ideal for navigation tasks, and greatly facilitate stable high-speed wall following

Locomotion Control of Hexapod Walking Robot with Four Degrees of Freedom per Leg

V této práci představujeme nového šestinohého robota jménem HAntR, kterého jsme vytvořili dle potřeb Laboratoře výpočetní robotiky Centra umělé inteligence fakulty Elektrotechnické Českého vysokého učení technického v Praze. Jeho hlavním účelem jest vylepšit schopnosti pohybu v těžkém terénu původního robotu přidáním čtvrtého stupně volnosti každé noze. Na základě nově navržené nohy jsme také přepracovali celé tělo robotu tak, aby splnilo i další požadavky, jako například menší rozměry, či možnost osazení alespoň šesti Lithium-Iontovými monočlánky. V práci pečlivě popisujeme motivace a úvahy, které nás k výslednému návrhu vedly. Uvádíme řešení přímé i inverzní kinematické úlohy řešené pomocí podmínky na ideální orientaci konce nohy a uvažující i důležité kinematické singularity. Navržený robot byl vyzkoušen v několika experimentech, při kterých byl použit námi navržený řídicí systém napsaný v jazyce C++. Ukázalo se, že HAntR vydrží díky zvýšené energetické hustotě a lepšímu rozkladu sil v končetinách autonomně fungovat přes hodinu. Robot je také schopen jít rychlostí až 0.42m/s, což předčí mnohé srovnatelné roboty. Při experimentu, kdy robot stál na nakloněné rovině, bylo prokázáno zlepšení oproti předchozímu robotu. A také jsme dle pokynů této práce potvrdili, že i HAntR je schopen adaptivní chůze spoléhající pouze na poziční zpětnou vazbu.In this thesis a novel six-legged robot called HAntR is presented. The robot was developed according to needs of the Robotics Laboratory, at the Artificial Intelligent Center, Faculty of Electrical Engineering, Czech Technical University in Prague. Its main purpose is enhancing rough-terrain movement capabilities by upgrading a former design by adding fourth degree of freedom to each leg. We also revised robot torso to fit new leg design and incorporate other requirements such as smaller dimensions with space for at least six Lithium-Ion cells. We thoroughly describe motivations and considerations that led us to the presented particular solution. Further, the solutions of forward and inverse kinematic tasks with partial orientation constraint and important singularities avoidance are presented. The proposed design has been evaluated in several experimental deployments, which utilised developed software controller written in C++. Endurance tests showed, that HAntR is able to remotely operate for over an hour thanks to increased energy density. Maximal speed test resulted to 0.42m/s during tripod gait, which outpaces most of the comparable robotic platforms. Experiment where HAntR stood on platform with varying inclination showed qualitative improvement against former robot. Finally, in accord with the thesis assignment, we proved that HAntR is able to perform walking with adaptive gait using positional feedback only

Adaptive Locomotion: The Cylindabot Robot

Adaptive locomotion is an emerging field of robotics due to the complex interaction between the robot and its environment. Hybrid locomotion is where a robot has more than one mode of locomotion and potentially delivers the benefits of both, however, these advantages are often not quantified or applied to new scenarios. The classic approach is to design robots with a high number of degrees of freedom and a complex control system, whereas an intelligent morphology can simplify the problem and maintain capabilities. Cylindabot is designed to be a minimally actuated hybrid robot with strong terrain crossing capabilities. By limiting the number of motors, this reduces the robot's weight and means less reinforcement is needed for the physical frame or drive system. Cylindabot uses different drive directions to transform between using wheels or legs. Cylindabot is able to climb a slope of 32 degrees and a step ratio of 1.43 while only being driven by two motors. A physical prototype and simulation models show that adaptation is optimal for a range of terrain (slopes, steps, ridges and gaps). Cylindabot successfully adapts to a map environment where there are several routes to the target location. These results show that a hybrid robot can increase its terrain capabilities when changing how it moves and that this adaptation can be applied to wider environments. This is an important step to have hybrid robots being deployed to real situations