Development of Grousers with a Tactile Sensor for Wheels of Lunar Exploration Rovers to Measure Sinkage

This paper presents a grouser developed for the wheels of lunar exploration rovers to measure sinkage. The wheels, which are intended to traverse loose soil such as lunar regolith, contain grousers that transfer thrust to the wheels and thus to the body of the rover. The interaction between the wheel (with grousers) and the loose soil can be described using a kinematic model. When traversing loose soil, the wheel sinks into the soil, which necessitates knowledge of the entrance angle needed in order to avoid this problem. If the entrance angle is known, the sinkage can be measured in real time before adverse conditions occur. Because of the importance and usefulness of detecting the entrance angle of the wheel, we herein propose a grouser with an embedded tactile sensor. A strain gauge on the surface of the grousers serves as the tactile sensor. In order to confirm the precision of the proposed grouser, we have performed tests on a rigid surface and loose soil surfaces.ArticleINTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS. 11:49 (2014)journal articl

System of Terrain Analysis, Energy Estimation and Path Planning for Planetary Exploration by Robot Teams

NASA’s long term plans involve a return to manned moon missions, and eventually sending humans to mars. The focus of this project is the use of autonomous mobile robotics to enhance these endeavors. This research details the creation of a system of terrain classification, energy of traversal estimation and low cost path planning for teams of inexpensive and potentially expendable robots. The first stage of this project was the creation of a model which estimates the energy requirements of the traversal of varying terrain types for a six wheel rocker-bogie rover. The wheel/soil interaction model uses Shibly’s modified Bekker equations and incorporates a new simplified rocker-bogie model for estimating wheel loads. In all but a single trial the relative energy requirements for each soil type were correctly predicted by the model. A path planner for complete coverage intended to minimize energy consumption was designed and tested. It accepts as input terrain maps detailing the energy consumption required to move to each adjacent location. Exploration is performed via a cost function which determines the robot’s next move. This system was successfully tested for multiple robots by means of a shared exploration map. At peak efficiency, the energy consumed by our path planner was only 56% that used by the best case back and forth coverage pattern. After performing a sensitivity analysis of Shibly’s equations to determine which soil parameters most affected energy consumption, a neural network terrain classifier was designed and tested. The terrain classifier defines all traversable terrain as one of three soil types and then assigns an assumed set of soil parameters. The classifier performed well over all, but had some difficulty distinguishing large rocks from sand. This work presents a system which successfully classifies terrain imagery into one of three soil types, assesses the energy requirements of terrain traversal for these soil types and plans efficient paths of complete coverage for the imaged area. While there are further efforts that can be made in all areas, the work achieves its stated goals

Mobility Evaluation of Wheeled Robots on Soft Terrain: Effect of Internal Force Distribution

[Abstract] Many applications of wheeled robots include operations in unstructured environments. Optimizing vehicle mobility is of key importance in these cases. Reduced mobility can limit the ability of the robot to achieve the mission goals and can even render it immobile in extreme cases. In this paper, some aspects of the effect of the wheel–ground interaction force distribution on mobility are investigated. A performance index based on the normal force distribution is used to compare different design layouts and vehicle configurations. The validity of this index was assessed using both multibody dynamics simulation and experimental results obtained with a six-wheeled rover prototype. Results confirmed that modifying the system configuration and employing active suspensions to alter the normal force distribution can lead to an increase of traction force available at the wheel–terrain interfaces, thus improving rover mobility. Finally, the study was extended to consider the change of soil properties during operation due to the multipass effect. Optimum load distributions were obtained as the solution of a constrained maximization problem.MINECO; JCI-2012-1237

A novel method of sensing and classifying terrain for autonomous unmanned ground vehicles

Unmanned Ground Vehicles (UGVs) play a vital role in preserving human life during hostile military operations and extend our reach by exploring extraterrestrial worlds during space missions. These systems generally have to operate in unstructured environments which contain dynamic variables and unpredictable obstacles, making the seemingly simple task of traversing from A-B extremely difficult. Terrain is one of the biggest obstacles within these environments as it could potentially cause a vehicle to become stuck and render it useless, therefore autonomous systems must possess the ability to directly sense terrain conditions. Current autonomous vehicles use look-ahead vision systems and passive laser scanners to navigate a safe path around obstacles; however these methods lack detail when considering terrain as they make predictions using estimations of the terrain’s appearance alone. This study establishes a more accurate method of measuring, classifying and monitoring terrain in real-time. A novel instrument for measuring direct terrain features at the wheel-terrain contact interface is presented in the form of the Force Sensing Wheel (FSW). Additionally a classification method using unique parameters of the wheel-terrain interaction is used to identify and monitor terrain conditions in real-time. The combination of both the FSW and real-time classification method facilitates better traversal decisions, creating a more Terrain Capable system

Planetary Rover Inertial Navigation Applications: Pseudo Measurements and Wheel Terrain Interactions

Accurate localization is a critical component of any robotic system. During planetary missions, these systems are often limited by energy sources and slow spacecraft computers. Using proprioceptive localization (e.g., using an inertial measurement unit and wheel encoders) without external aiding is insufficient for accurate localization. This is mainly due to the integrated and unbounded errors of the inertial navigation solutions and the drifted position information from wheel encoders caused by wheel slippage. For this reason, planetary rovers often utilize exteroceptive (e.g., vision-based) sensors. On the one hand, localization with proprioceptive sensors is straightforward, computationally efficient, and continuous. On the other hand, using exteroceptive sensors for localization slows rover driving speed, reduces rover traversal rate, and these sensors are sensitive to the terrain features. Given the advantages and disadvantages of both methods, this thesis focuses on two objectives. First, improving the proprioceptive localization performance without significant changes to the rover operations. Second, enabling adaptive traversability rate based on the wheel-terrain interactions while keeping the localization reliable. To achieve the first objective, we utilized the zero-velocity, zero-angular rate updates, and non-holonomicity of a rover to improve rover localization performance even with the limited available sensor usage in a computationally efficient way. Pseudo-measurements generated from proprioceptive sensors when the rover is stationary conditions and the non-holonomic constraints while traversing can be utilized to improve the localization performance without any significant changes to the rover operations. Through this work, it is observed that a substantial improvement in localization performance, without the aid of additional exteroceptive sensor information. To achieve the second objective, the relationship between the estimation of localization uncertainty and wheel-terrain interactions through slip-ratio was investigated. This relationship was exposed with a Gaussian process with time series implementation by using the slippage estimation while the rover is moving. Then, it is predicted when to change from moving to stationary conditions by mapping the predicted slippage into localization uncertainty prediction. Instead of a periodic stopping framework, the method introduced in this work is a slip-aware localization method that enables the rover to stop more frequently in high-slip terrains whereas stops rover less frequently for low-slip terrains while keeping the proprioceptive localization reliable

Terrain Aware Traverse Planning for Mars Rovers

NASA is proposing a Mars Sample Return mission, to be completed within one Martian year, that will require enhanced autonomy to perform its duties faster, safer, and more efficiently. With its main purpose being to retrieve samples possibly tens of kilometers away, it will need to drive beyond line-of-sight to get to its target more quickly than any rovers before. This research proposes a new methodology to support a sample return mission and is divided into three compo-nents: map preparation (map of traversability, i.e., ability of a terrain to sustain the traversal of a vehicle), path planning (pre-planning and replanning), and terrain analysis. The first component aims at creating a better knowledge of terrain traversability to support planning, by predicting rover slip and drive speed along the traverse using orbital data. By overlapping slope, rock abundance and terrain types at the same location, the expected drive velocity is obtained. By combining slope and thermal data, additional information about the experienced slip is derived, indicating whether it will be low (less than 30%) or medium to high (more than 30%). The second component involves planning the traverse for one Martian day (or sol) at a time, based on the map of expected drive speed. This research proposes to plan, offline, several paths traversable in one sol. Once online, the rover chooses the fastest option (the path cost being calculated using the distance divided by the expected velocity). During its drive, the rover monitors the terrain via analysis of its experienced wheel slip and actual speed. This information is then passed along the different pre-planned paths over a given distance (e.g., 25 m) and the map of traversability is locally updated given this new knowledge. When an update occurs, the rover calculates the new time of arrival of the various paths and replans its route if necessary. When tested in a simulation study on maps of the Columbia Hills, Mars, the rover successfully updates the map given new information drawn from a modified map used as ground truth for simulation purposes and replans its traverse when needed. The third component describes a method to assess the soil in-situ in case of dangerous terrain detected during the map update, or if the monitoring is not enough to confirm the traversability predicted by the map. The rover would deploy a shear vane instrument to compute intrinsic terrain parameters, information then propagated ahead of the rover to update the map and replan if necessary. Experiments in a laboratory setting as well as in the field showed promising results, the mounted shear vane giving values close to the expected terrain parameters of the tested soils

Methods for the improvement of power resource prediction and residual range estimation for offroad unmanned ground vehicles

Unmanned Ground Vehicles (UGVs) are becoming more widespread in their deployment. Advances in technology have improved not only their reliability but also their ability to perform complex tasks. UGVs are particularly attractive for operations that are considered unsuitable for human operatives. These include dangerous operations such as explosive ordnance disarmament, as well as situations where human access is limited including planetary exploration or search and rescue missions involving physically small spaces. As technology advances, UGVs are gaining increased capabilities and consummate increased complexity, allowing them to participate in increasingly wide range of scenarios. UGVs have limited power reserves that can restrict a UGV’s mission duration and also the range of capabilities that it can deploy. As UGVs tend towards increased capabilities and complexity, extra burden is placed on the already stretched power resources. Electric drives and an increasing array of processors, sensors and effectors, all need sufficient power to operate. Accurate prediction of mission power requirements is therefore of utmost importance, especially in safety critical scenarios where the UGV must complete an atomic task or risk the creation of an unsafe environment due to failure caused by depleted power. Live energy prediction for vehicles that traverse typical road surfaces is a wellresearched topic. However, this is not sufficient for modern UGVs as they are required to traverse a wide variety of terrains that may change considerably with prevailing environmental conditions. This thesis addresses the gap by presenting a novel approach to both off and on-line energy prediction that considers the effects of weather conditions on a wide variety of terrains. The prediction is based upon nonlinear polynomial regression using live sensor data to improve upon the accuracy provided by current methods. The new approach is evaluated and compared to existing algorithms using a custom ‘UGV mission power’ simulation tool. The tool allows the user to test the accuracy of various mission energy prediction algorithms over a specified mission routes that include a variety of terrains and prevailing weather conditions. A series of experiments that test and record the ‘real world’ power use of a typical small electric drive UGV are also performed. The tests are conducted for a variety of terrains and weather conditions and the empirical results are used to validate the results of the simulation tool. The new algorithm showed a significant improvement compared with current methods, which will allow for UGVs deployed in real world scenarios where they must contend with a variety of terrains and changeable weather conditions to make accurate energy use predictions. This enables more capabilities to be deployed with a known impact on remaining mission power requirement, more efficient mission durations through avoiding the need to maintain excessive estimated power reserves and increased safety through reduced risk of aborting atomic operations in safety critical scenarios. As supplementary contribution, this work created a power resource usage and prediction test bed UGV and resulting data-sets as well as a novel simulation tool for UGV mission energy prediction. The tool implements a UGV model with accurate power use characteristics, confirmed by an empirical test series. The tool can be used to test a wide variety of scenarios and power prediction algorithms and could be used for the development of further mission energy prediction technology or be used as a mission energy planning tool

Reconfigurability in space systems : architecting framework and case studies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.Includes bibliographical references (p. 247-257).Reconfigurability in engineered systems is of increasing interest particularly in Aerospace Systems since it allows for resource efficiency, evolvability, and enhanced survivability. Although it is often regarded as a desirable quality for a system, it has traditionally been difficult to quantitatively analyze its effects on various system properties in the early design stage. In order to allow for gaining an in-depth understanding of the various aspects of reconfigurability and its relationship with a system's architecture, a framework encompassing a set of definitions, metrics, and methods has been proposed. Two different modeling schemes, based on Markov models and controls theory, are first developed to show how the states and time aspects of reconfigurable systems can be naturally modeled and studied. An analytical model for quantifying the effect of reconfigurability on mission logistics, specifically spare parts demands, is formulated and it is shown through one specific example that reconfigurable parts can allow for 33-50% mass reduction. The system availability, however, becomes very sensitive to the reliability of the parts. Two case studies are then used for detailed illustration of the application of the developed framework.(cont.) In the first case study, the effect of reconfigurability on a fleet of planetary surface vehicles for a surface exploration mission are analyzed. It is found that a fleet of reconfigurable vehicles can allow for a mass savings of up to 27% and their expected transport capability degradation is almost three times lower as compared to a fleet of non-reconfigurable vehicles. In the second case-study, the reconfiguration of low earth-orbit communication satellite constellations is considered for evolving to higher capacity levels. It is found that reconfiguring a previously deployed constellation can be a viable option only for certain capacity levels and multi-payload launch capability scenarios. In addition to the high level 'ility' perspectives, a lower level design assessment is also carried out through a survey of 33 representative reconfigurable systems. It is found that on average, for commercial items the cost of reconfigurability is 35%, and the average useful state occupancy time is always at least 10 times the reconfiguration time of the system. Based on the illustrative results of the case studies, and generalization of empirical data, a few principles and guidelines for design for reconfigurability are proposed.by Afreen Siddiqi.Ph.D

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version