A novel concept for analysis and performance evaluation of wheeled rovers

[Abstract] - The analysis, design, and operation planning of rovers are often based on predictive dynamic simulation, where the multibody model of the vehicle is combined with terramechanics relations for the representation of the wheel–ground interaction. There are, however, limitations in terramechanics models that prevent their use in parametric analysis and simulation studies. Increasing mobility is generally a primary objective for the design and operation of rovers. The models and assumptions used in the analysis phase should target this objective. In this paper we put forward a new concept for the analysis of wheeled rovers, particularly for applications in off-road environments on soft soil. We propose a novel view of the problem based on the development of models that are primarily intended to represent how parameter changes in the robot design can influence performance. These models allow for the definition of indicators, which gives information about the behavior of the system. We term such models observative. In the reported work, a set of indicators for rover performance is formulated using such models. The ability of these indicators to characterize the behavior of a rover is assessed with a series of simulation tests and experiments. The indicators defined using observative models succeeded to capture the changes in rover performance due to variations in the system parameters. Results show that the proposed models can provide a useful tool for the design and operation of planetary exploration rovers

System Design, Motion Modelling and Planning for a Recon figurable Wheeled Mobile Robot

Over the past ve decades the use of mobile robotic rovers to perform in-situ scienti c investigations on the surfaces of the Moon and Mars has been tremendously in uential in shaping our understanding of these extraterrestrial environments. As robotic missions have evolved there has been a greater desire to explore more unstructured terrain. This has exposed mobility limitations with conventional rover designs such as getting stuck in soft soil or simply not being able to access rugged terrain. Increased mobility and terrain traversability are key requirements when considering designs for next generation planetary rovers. Coupled with these requirements is the need to autonomously navigate unstructured terrain by taking full advantage of increased mobility. To address these issues, a high degree-of-freedom recon gurable platform that is capable of energy intensive legged locomotion in obstacle-rich terrain as well as wheeled locomotion in benign terrain is proposed. The complexities of the planning task that considers the high degree-of-freedom state space of this platform are considerable. A variant of asymptotically optimal sampling-based planners that exploits the presence of dominant sub-spaces within a recon gurable mobile robot's kinematic structure is proposed to increase path quality and ensure platform safety. The contributions of this thesis include: the design and implementation of a highly mobile planetary analogue rover; motion modelling of the platform to enable novel locomotion modes, along with experimental validation of each of these capabilities; the sampling-based HBFMT* planner that hierarchically considers sub-spaces to better guide search of the complete state space; and experimental validation of the planner with the physical platform that demonstrates how the planner exploits the robot's capabilities to uidly transition between various physical geometric con gurations and wheeled/legged locomotion modes

On the Suspension Design of Paquitop, a Novel Service Robot for Home Assistance Applications

The general and constant ageing of the world population that has been observed in the last decade has led robotics researchers community to focus its aims to answer the ever-growing demand for health care, housing, care-giving, and social security. Among others, the researchers at Politecnico di Torino are developing a novel platform to enhance the performance offered by present-day issues, and to assess many others which were not even taken into consideration before they have been highlighted by the pandemic emergency currently in progress. This situation, in fact, made dramatically clear how important it is to have reliable non-human operators whom one can trust when the life of elderly or weak patients is endangered by the simple presence of other people. The platform, named Paquitop, features an innovative architecture conceived for omni-directional planar motion. The machine is designed for domestic, unstructured, and variously populated environments. Therefore, the mobile robot should be able to avoid or pass over small obstacles, passing through the capability to achieve specific person tracking tasks, and arriving to the need of operating with an high dynamic performance. Given its purpose, this work addresses the design of the suspension system which enables the platform to ensure a steady floor contact and adequate stability in every using condition. Different configurations of such system are then presented and compared through use-case simulations

Lunar Surface Systems Supportability Technology Development Roadmap

The Lunar Surface Systems Supportability Technology Development Roadmap is a guide for developing the technologies needed to enable the supportable, sustainable, and affordable exploration of the Moon and other destinations beyond Earth. Supportability is defined in terms of space maintenance, repair, and related logistics. This report considers the supportability lessons learned from NASA and the Department of Defense. Lunar Outpost supportability needs are summarized, and a supportability technology strategy is established to make the transition from high logistics dependence to logistics independence. This strategy will enable flight crews to act effectively to respond to problems and exploit opportunities in an environment of extreme resource scarcity and isolation. The supportability roadmap defines the general technology selection criteria. Technologies are organized into three categories: diagnostics, test, and verification; maintenance and repair; and scavenge and recycle. Furthermore, "embedded technologies" and "process technologies" are used to designate distinct technology types with different development cycles. The roadmap examines the current technology readiness level and lays out a four-phase incremental development schedule with selection decision gates. The supportability technology roadmap is intended to develop technologies with the widest possible capability and utility while minimizing the impact on crew time and training and remaining within the time and cost constraints of the program

Enabling All-Access Mobility for Planetary Exploration Vehicles via Transformative Reconfiguration

Effective large-scale exploration of planetary surfaces requires robotic vehicles capable of mobility across chaotic terrain. Characterized by a combination of ridges, cracks and valleys, the demands of this environment can cause spacecraft to experience significant reductions in operating footprint, performance, or even result in total system loss. Significantly increasing the scientific return of an interplanetary mission is facilitated by architectures capable of real-time configuration changes that go beyond that of active suspensions while concurrently meeting system, mass, power, and cost constraints. This Phase 1 report systematically explores how in-service architecture changes can expand system capabilities and mission opportunities. A foundation for concept generation is supplied by four Martian mission profiles spanning chasms, ice fields, craters and rocky terrain. A fifth mission profile centered on Near Earth Object exploration is also introduced. Concept generation is directed using four transformation principles - a taxonomy developed by the engineering design community to explain the cause of an architecture change and existing brainstorming techniques. This allowed early conceptual sketches of architecture changes to be organized by the principle driving the greatest increase in mission performance capability

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Multi-axle Vehicle Modeling and Stability Control: A Reconfigurable Approach

Multi-axle vehicles, such as trucks and buses, have been playing a vital role in trucking industry, public transportation system, and long-distance transport services. However, at the same time, statistics suggest more than one million lives are lost in road accidents each year over the world. The high adoption and utilization of multi-axle vehicles hold a significant portion of road accidents and death. To improve the active safety of vehicles, active systems have been developed and commercialized over the last decades to augment the driver's actions. However, unlike two-axle vehicles (e.g., passenger cars), multi-axle vehicles come in a rich diversity and variety to meet with many different transportation needs. Specifically, vehicle configurations are seen in different numbers of axles, numbers of articulations, powertrain modes, and active actuation systems. In addition, multi-axle vehicles are usually articulated, which makes the dynamics and control more complex and challenging as more instability modes appear, such as, trailer sway and jackknife. This research is hence motivated by an essential question: how can a universal and reconfigurable control system be developed for any multi-axle/articulated vehicle with any configuration? Leveraging the matrix approach and optimization-based techniques, this thesis developed a reconfigurable and universal modeling and control framework to this aim. Specifically, a general dynamics modeling that unifies any multi-axle and articulated vehicles in one formulation is developed in an intuitive manner. It defines the `Boolean Matrices' to determine any configuration of the articulation, the number of axles, and the active actuation systems. In this way, the corresponding dynamics model can be easily and quickly formulated when axles, articulations or actuators are added or removed. The general modeling serves to achieve the universality and reconfigurability in controller design. Therefore, a hierarchical, i.e., two-layer, control system is proposed. In the high layer, the optimization process of a model predictive control (MPC) calculates corrective Center of Gravity (CG) forces/moments, which are universal to any vehicle. The lower-level controller is achieved by a Control Allocation (CA) algorithm. It aims to realize the MPC commands by regulating the steering or torque (driving or braking) at each wheel optimally. In addition, the optimization takes into account real-time constraints, such as actuator limits, tire capacity, wheel slips, and actuators failure. Simulations are conducted on different vehicle configurations to evaluate control performance, reconfigurability, and robustness of the system. Additionally, to evaluate the real-time performance of the developed controller, experimental validation is carried out on an articulated vehicle with multiple configurations of differential braking systems. It is observed that the controller is very effective in dynamics control and has a promising reconfigurability when moving from one configuration to another

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences