Benefit of "Push-pull" Locomotion for Planetary Rover Mobility

As NASAs exploration missions on planetary terrains become more aggressive, a focus on alternative modes of locomotion for rovers is necessary. In addition to climbing steep slopes, the terrain in these extreme environments is often unknown and can be extremely hard to traverse, increasing the likelihood of a vehicle or robot becoming damaged or immobilized. The conventional driving mode in which all wheels are either driven or free-rolling is very efficient on flat hard ground, but does not always provide enough traction to propel the vehicle through soft or steep terrain. This paper presents an alternative mode of travel and investigates the fundamental differences between these locomotion modes. The methods of push-pull locomotion discussed can be used with articulated wheeled vehicles and are identified as walking or inchinginch-worming. In both cases, the braked non-rolling wheels provide increased thrust. An in-depth study of how soil reacts under a rolling wheel vs. a braked wheel was performed by visually observing the motion of particles beneath the surface. This novel technique consists of driving or dragging a wheel in a soil bin against a transparent wall while high resolution, high-rate photographs are taken. Optical flow software was then used to determine shearing patterns in the soil. Different failure modes were observed for the rolling and braked wheel cases. A quantitative comparison of inching vs. conventional driving was also performed on a full-scale vehicle through a series of drawbar pull tests in the Lunar terrain strength simulant, GRC-1. The effect of tire stiffness was also compared; typically compliant tires provide better traction when driving in soft soil, however its been observed that rigid wheels may provide better thrust when non-rolling. Initial tests indicate up to a possible 40 increase in pull force capability at high slip when inching vs. rolling

Design and Development of an Inspection Robotic System for Indoor Applications

The inspection and monitoring of industrial sites, structures, and infrastructure are important issues for their sustainability and further maintenance. Although these tasks are repetitive and time consuming, and some of these environments may be characterized by dust, humidity, or absence of natural light, classical approach relies on large human activities. Automatic or robotic solutions can be considered useful tools for inspection because they can be effective in exploring dangerous or inaccessible sites, at relatively low-cost and reducing the time required for the relief. The development of a paradigmatic system called Inspection Robotic System (IRS) is the main objective of this paper to demonstrate the feasibility of mechatronic solutions for inspection of industrial sites. The development of such systems will be exploited in the form of a tool kit to be flexible and installed on a mobile system, in order to be used for inspection and monitoring, possibly introducing high efficiency, quality and repetitiveness in the related sector. The interoperability of sensors with wireless communication may form a smart sensors tool kit and a smart sensor network with powerful functions to be effectively used for inspection purposes. Moreover, it may constitute a solution for a broad range of scenarios spacing from industrial sites, brownfields, historical sites or sites dangerous or difficult to access by operators. First experimental tests are reported to show the engineering feasibility of the system and interoperability of the mobile hybrid robot equipped with sensors that allow real-time multiple acquisition and storage

Push-Pull Locomotion for Vehicle Extrication

For applications in which unmanned vehicles must traverse unfamiliar terrain, there often exists the risk of vehicle entrapment. Typically, this risk can be reduced by using feedback from on-board sensors that assess the terrain. This work addressed the situations where a vehicle has already become immobilized or the desired route cannot be traversed using conventional rolling. Specifically, the focus was on using push-pull locomotion in high sinkage granular material. Push-pull locomotion is an alternative mode of travel that generates thrust through articulated motion, using vehicle components as anchors to push or pull against. It has been revealed through previous research that push-pull locomotion has the capacity for generating higher net traction forces than rolling, and a unique optical flow technique indicated that this is the result of a more efficient soil shearing method. It has now been found that pushpull locomotion results in less sinkage, lower travel reduction, and better power efficiency in high sinkage material as compared to rolling. Even when starting from an "entrapped" condition, push-pull locomotion was able to extricate the test vehicle. It is the authors' recommendation that push-pull locomotion be considered as a reliable back-up mode of travel for applications where terrain entrapment is a possibility

Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing

As NASA strives to explore the surface of the Moon and Mars, there is a continued need for improved tire and vehicle development. When tires or vehicles are being designed for off-road conditions where significant thrust generation is required, such as climbing out of craters on the Moon, it is important to use a standard test method for evaluating their tractive performance. The drawbar pull (DP) test is a way of measuring the net thrust generated by tires or a vehicle with respect to performance metrics such as travel reduction, sinkage, or power efficiency. DP testing may be done using a single tire on a traction rig, or with a set of tires on a vehicle; this report focuses on vehicle DP tests. Though vehicle DP tests have been used for decades, there are no standard procedures that apply to exploration vehicles. This report summarizes previous methods employed, shows the sensitivity of certain test parameters, and provides a body of knowledge for developing standard testing procedures. The focus of this work is on lunar applications, but these test methods can be applied to terrestrial and planetary conditions as well. Section 1.0 of this report discusses the utility of DP testing for off-road vehicle evaluation and the metrics used. Section 2.0 focuses on test-terrain preparation, using the example case of lunar terrain. There is a review of lunar terrain analogs implemented in the past and a discussion on the lunar terrain conditions created at the NASA Glenn Research Center, including methods of evaluating the terrain strength variation and consistency from test to test. Section 3.0 provides details of the vehicle test procedures. These consist of a review of past methods, a comprehensive study on the sensitivity of test parameters, and a summary of the procedures used for DP testing at Glenn

Study of Mobile Robot Operations Related to Lunar Exploration

Mobile robots extend the reach of exploration in environments unsuitable, or unreachable, by humans. Far-reaching environments, such as the south lunar pole, exhibit lighting conditions that are challenging for optical imagery required for mobile robot navigation. Terrain conditions also impact the operation of mobile robots; distinguishing terrain types prior to physical contact can improve hazard avoidance. This thesis presents the conclusions of a trade-off that uses the results from two studies related to operating mobile robots at the lunar south pole. The lunar south pole presents engineering design challenges for both tele-operation and lidar-based autonomous navigation in the context of a near-term, low-cost, short-duration lunar prospecting mission. The conclusion is that direct-drive tele-operation may result in improved science data return. The first study is on demonstrating lidar reflectance intensity, and near-infrared spectroscopy, can improve terrain classification over optical imagery alone. Two classification techniques, Naive Bayes and multi-class SVM, were compared for classification errors. Eight terrain types, including aggregate, loose sand and compacted sand, are classified using wavelet-transformed optical images, and statistical values of lidar reflectance intensity. The addition of lidar reflectance intensity was shown to reduce classification errors for both classifiers. Four types of aggregate material are classified using statistical values of spectral reflectance. The addition of spectral reflectance was shown to reduce classification errors for both classifiers. The second study is on human performance in tele-operating a mobile robot over time-delay and in lighting conditions analogous to the south lunar pole. Round-trip time delay between operator and mobile robot leads to an increase in time to turn the mobile robot around obstacles or corners as operators tend to implement a `wait and see\u27 approach. A study on completion time for a cornering task through varying corridor widths shows that time-delayed performance fits a previously established cornering law, and that varying lighting conditions did not adversely affect human performance. The results of the cornering law are interpreted to quantify the additional time required to negotiate a corner under differing conditions, and this increase in time can be interpreted to be predictive when operating a mobile robot through a driving circuit

Autonomous Soil Assessment System for Planetary Rovers

Planetary rovers face mobility hazards associated with various classes of terrains they traverse, and hence it is desirable to enable remote prediction of terrain trafficability (ability to traverse) properties. For that reason, the development of algorithms for assessing terrain type and mobility properties, as well as for coupling these data in an online learning framework, represent important capabilities for next-generation rovers. This work focuses mainly on 3-way terrain classification (classifying as one of the types: Sand, Bedrock and Gravel) as well as on the correlation of terrain types and their mobility properties in a framework that enables online learning. For terrain classification, visual descriptors are developed, which are primarily based on visual texture and are captured in form of histograms of edge filter responses at various scales and orientations. The descriptors investigated in this work are HOG (Histogram of Oriented Gradients), GIST, MR8 (Maximum Response) Textons and the classification techniques implemented here are nearest and k-nearest neighbors. Further, monochrome image intensity is used as an additional feature to further distinguish bedrock from the other terrain types. No major differences in performance are observed between the three descriptors, leading to the adoption of the HOG approach due to its lower computational complexity (over 3 orders of magnitude difference in complexity between HOG and Textons) and thus higher applicability to planetary missions. Tests demonstrate an accuracy between 70% and 93% (81% average) for the classification using the HOG descriptor, on images taken by NASA’s Mars rovers. To predict terrain trafficability ahead of the rover, exteroceptive data namely terrain type and slope, are correlated with the trafficability metrics namely slip, sinkage and roughness, in a learning framework. A queue based data structure has been implemented for the correlation, which keeps discarding the older data so as to avoid diminishing the effect of newer data samples, when there is a large amount of data. This also ensures that the rover will be able to adapt to changing terrains responses and predict the risk level (low, medium or high) accordingly. Finally, all the algorithms developed in this work were tested and verified in a field test demo at the CSA (Canadian Space Agency) mars yard. The risk metric in combination with the queue based data structure, can achieve stable predictions in consistent terrains, while also being responsive to sudden changes in terrain trafficability

Energy-Efficient Trajectory Planning for Skid-Steer Rovers

A skid-steer rover’s power consumption is highly dependent on the turning radius of its path. For example, a point turn consumes a lot of power compared to a straight-line motion. Thus, in path planning for this kind of rover, turning radius is a factor that should be considered explicitly. Based on the literature, there is a lack of analytical approach for finding energy-optimal paths for skid-steer rovers. This thesis addresses this problem for such rovers, specifically on obstacle-free hard ground. The equivalency theorem in this thesis indicates that, when using a popular power model for skid-steer rovers on hard ground, all minimum-energy solutions follow the same path irrespective of velocity constraints that may or may not be imposed. This non-intuitive result stems from the fact that with this model of the system the total energy is fully parametrized by the geometry of the path alone. It is shown that one can choose velocity constraints to enforce constant power consumption, thus transforming the energy-optimal problem to an equivalent time-optimal problem. Existing theory, built upon the basis of Pontryagin’s minimum principle to find the extremals for time-optimal trajectories for a rigid body, can then be used to solve the problem. Accordingly, the extremal paths are obtained for the energy-efficient path planning problem. As there is a finite number of extremals, they are enumerated to find the minimum-energy path for a particular example. Moreover, the analysis identifies that the turns in optimal paths (aside from a small number of special cases called whirls) are to be circular arcs of a particular turning radius, R′, equal to half of a skid-steer rover’s slip track. R′ is the turning radius at which the inner wheels of a skid-steer rover are not commanded to turn, and its description and the identification of its paramount importance in energy-optimal path planning are investigated. Experiments with a Husky UGV rover validate the energy-optimality of using R′ turns. Furthermore, a practical velocity constraint for skid-steer rovers is proposed that maintains constant forward velocity above R’ and constant angular velocity below it. Also, in separate but related work, it is shown that almost always equal “friction requirement” can be used to obtain optimal traction forces for a common and practical type of 4-wheel rover

Analysis of inverse simulation algorithms with an application to planetary rover guidance and control

Rover exploration is a contributing factor to driving the relevant research forward on guidance, navigation, and control (GNC). Yet, there is a need for incorporating the dynamic model into the controller for increased accuracy. Methods that use the model are limited by issues such as linearity, systems affine in the control, number of inputs and outputs. Inverse Simulation is a more general approach that uses a mathematical model and a numerical scheme to calculate the control inputs necessary to produce a desired response defined using the output variables. This thesis develops the Inverse Simulation algorithm for a general state space model and utilises a numerical Newton-Raphson scheme to converge to the inputs using two approaches: The Differentiation method converges based on the state and output equations. The Integration method converges based on whether the output matches the desired and is suitable for grey or black-box models. The thesis offers extensive insights into the requirements and application of Inverse Simulation and the performance parameters. Attention is given to how the inputs and outputs affect the Jacobian formulation and ensure an efficient solution. The linear case and the relationship with feedback linearisation are examined. Examples are given using simple mechanical systems and an example is also given as to how Inverse Simulation can be used for determining system input disturbances. Inverse Simulation is applied for the first time for guidance and control of a fourwheeled, differentially driven rover. The desired output is the time history of the desired trajectory and is used to produce the required control inputs. The control inputs are nominal and are applied to the rover without additional correction. Using insights from the system’s physics and actuation, the Differentiation and Integration schemes are developed based on the general method presented in this thesis. The novel Differentiation scheme employs a non-square Jacobian. The method provides very accurate position and orientation control of the rover while considering the limitations of the model used. Finally, the application of Inverse Simulation to the rover is supported by a review of current designs that resulted in a rover taxonomy