Traction Modeling and Control of a Differential Drive Mobile Robot to Avoid Wheel Slip

The motion of a differential drive mobile robot with consideration of slip at contact between the wheels and the ground is studied in this work. Traction forces between the wheel and the ground are derived by considering a rigid wheel, rigid ground interaction model and a caster wheel which provides support to the mobile robot during motion. The motion governing equations are determined by incorporating the traction forces. Numerical simulations are conducted to learn the motion behavior of the robot with wheel slip for a range of wheel input torques. Based on the traction force model and observations from numerical simulations, a slip avoidance controller that limits the input torques is developed. Experiments are conducted to verify the characteristics of the dynamic model with slip and the control strategy used to avoid slip. Models that describe the dynamics of a differential drive mobile robot with and without slip are presented and discussed. A traction force model is developed by considering a simple Coulomb friction model. The caster wheel plays an important role in determining the traction forces. The longitudinal and lateral velocities of the wheel are used to compute the longitudinal and lateral forces. Wheel slip occurs if the reaction force exerted by the applied torque is greater than the static frictional force, which is calculated by the proposed model and this limit is used to implement a slip avoidance controller. Numerical simulations and experiments of the system using the proposed traction model reveal that the angular velocity of the wheels is greater than the corresponding linear velocity when slip occurs. The proposed torque limiting controller to avoid slip is also implemented in numerical simulations and experiments. Experimental results show a good correlation with the numerical simulations, thus verifying the approach and the developed dynamic model with wheel slip.Mechanical Engineerin

Design characteristics of a pipe crawling robot

This thesis deals with the design characteristics of a pipe crawling vehicle which utilises a unique, innovative and patented drive system. The principle of the drive system is simple. That is, if a brush is inserted into a pipe and its bristles are swept back at an angle, then, it is easier to push the brush forwards through the pipe than it is to pull it backwards. Thus, if two brushes are interconnected by a reciprocating cylinder, then, by cycling the cylinder, it is possible for the vehicle to "crawl" through the pipe. The drive mechanism has two main advantages. The first is the ability of the bristles to deflect over or around obstacles, thus, the vehicles can be used in severely damaged pipes. Secondly, the drive mechanism is able to generate extremely high "grip" forces, thus, the vehicle has a high payload to weight ratio. This "simple" traction mechanism has subsequently been proven to be extremely capable in significantly hostile environments, for example, nuclear plants and sewers. The development of the vehicle has resulted in brushes being considered as "engineering" components. This thesis considers the forces present when a brush moves forward through a pipe, further, it also considers the forces present if the brush is required to grip the walls of the pipe. A "simple" cantilever model has been developed which predicts the force required to push a brush forwards through the pipe. A second model has been developed which predicts the forward to reverse or "slip" to "grip" ratio of a brush, for given functional conditions. This model is deemed satisfactory up to the onset of bristle buckling. The experimental program determined three factors, they were, the force required to load a brush into a pipe, the force required to push a brush forward through a pipe and the reverse force a brush could support prior to failure. It can be concluded that this vehicle, through its tractive capability arid environmental compliance, is able to traverse irregularly shaped pipes. Ultimately, this allows tooling to be transported and used at previously unobtainable positions within such pipes

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

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

Development, Control, and Empirical Evaluation of the Six-Legged Robot SpaceClimber Designed for Extraterrestrial Crater Exploration

In the recent past, mobile robots played an important role in the field of extraterrestrial surface exploration. Unfortunately, the currently available space exploration rovers do not provide the necessary mobility to reach scientifically interesting places in rough and steep terrain like boulder fields and craters. Multi-legged robots have proven to be a good solution to provide high mobility in unstructured environments. However, space missions place high demands on the system design, control, and performance which are hard to fulfill with such kinematically complex systems. This thesis focuses on the development, control, and evaluation of a six-legged robot for the purpose of lunar crater exploration considering the requirements arising from the envisaged mission scenario. The performance of the developed system is evaluated and optimized based on empirical data acquired in significant and reproducible experiments performed in a laboratory environment in order to show thecapability of the system to perform such a task and to provide a basis for the comparability with other mobile robotic solutions

Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

The Design and Development of a Mobile Colonoscopy Robot

The conventional colonoscopy is a common procedure used to access the colon. Despite it being considered the Gold Standard procedure for colorectal cancer diagnosis and treatment, it has a number of major drawbacks, including high patient discomfort, infrequent but serious complications and high skill required to perform the procedure. There are a number of potential alternatives to the conventional colonoscopy, from augmenting the colonoscope to using Computed Tomography Colonography (CTC) - a completely non-invasive method. However, a truly effective, all-round alternative has yet to be found. This thesis explores the design and development of a novel solution: a fully mobile colonoscopy robot called “RollerBall”. Unlike current passive diagnostic capsules, such as PillCam, this device uses wheels at the end of adjustable arms to provide locomotion through the colon, while providing a stable platform for the use of diagnostic and therapeutic tools. The work begins by reviewing relevant literature to better understand the problem and potential solutions. RollerBall is then introduced and its design described in detail. A robust prototype was then successfully fabricated using a 3D printing technique and its performance assessed in a series of benchtop experiments. These showed that the mechanisms functioned as intended and encouraged the further development of the concept. Next, the fundamental requirement of gaining traction on the colon was shown to be possible using hexagonal shaped, macro-scale tread patterns. A friction coefficient ranging between 0.29 and 0.55 was achieved with little trauma to the tissue substrate. The electronics hardware and control were then developed and evaluated in a series of tests in silicone tubes. An open-loop strategy was first used to establish the control algorithm to map the user inputs to motor outputs (wheel speeds). These tests showed the efficacy of the locomotion technique and the control algorithm used, but they highlighted the need for autonomy. To address this, feedback was included to automate the adjusting of the arm angle and amount of force applied by the device; a forward facing camera was also used to automate the orientation control by tracking a user-defined target. Force and orientation control were then combined to show that semi-autonomous control was possible and as a result, it was concluded that clinical use may be feasible in future developments

3D position tracking for all-terrain robots

Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. Such robots find their application in scientific exploration of hostile environments like deserts, volcanoes, in the Antarctic or on other planets. They are also of high interest for search and rescue operations after natural or artificial disasters. The challenges to bring autonomy to all terrain rovers are wide. In particular, it requires the development of systems capable of reliably navigate with only partial information of the environment, with limited perception and locomotion capabilities. Amongst all the required functionalities, locomotion and position tracking are among the most critical. Indeed, the robot is not able to fulfill its task if an inappropriate locomotion concept and control is used, and global path planning fails if the rover loses track of its position. This thesis addresses both aspects, a) efficient locomotion and b) position tracking in rough terrain. The Autonomous System Lab developed an off-road rover (Shrimp) showing excellent climbing capabilities and surpassing most of the existing similar designs. Such an exceptional climbing performance enables an extension in the range of possible areas a robot could explore. In order to further improve the climbing capabilities and the locomotion efficiency, a control method minimizing wheel slip has been developed in this thesis. Unlike other control strategies, the proposed method does not require the use of soil models. Independence from these models is very significant because the ability to operate on different types of soils is the main requirement for exploration missions. Moreover, our approach can be adapted to any kind of wheeled rover and the processing power needed remains relatively low, which makes online computation feasible. In rough terrain, the problem of tracking the robot's position is tedious because of the excessive variation of the ground. Further, the field of view can vary significantly between two data acquisition cycles. In this thesis, a method for probabilistically combining different types of sensors to produce a robust motion estimation for an all-terrain rover is presented. The proposed sensor fusion scheme is flexible in that it can easily accommodate any number of sensors, of any kind. In order to test the algorithm, we have chosen to use the following sensory inputs for the experiments: 3D-Odometry, inertial measurement unit (accelerometers, gyros) and visual odometry. The 3D-Odometry has been specially developed in the framework of this research. Because it accounts for ground slope discontinuities and the rover kinematics, this technique results in a reasonably precise 3D motion estimate in rough terrain. The experiments provided excellent results and proved that the use of complementary sensors increases the robustness and accuracy of the pose estimate. In particular, this work distinguishes itself from other similar research projects in the following ways: the sensor fusion is performed with more than two sensor types and sensor fusion is applied a) in rough terrain and b) to track the real 3D pose of the rover. Another result of this work is the design of a high-performance platform for conducting further research. In particular, the rover is equipped with two computers, a stereovision module, an omnidirectional vision system, an inertial measurement unit, numerous sensors and actuators and electronics for power management. Further, a set of powerful tools has been developed to speed up the process of debugging algorithms and analyzing data stored during the experiments. Finally, the modularity and portability of the system enables easy adaptation of new actuators and sensors. All these characteristics speed up the research in this field