Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

Using performance-based evaluation to close the loop between biological and robotic navigation

In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.

Virtual simulator for mobile robots navigation systems

This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

Fusing the Navigation Information of Dual Foot-Mounted Zero-Velocity-Update-Aided Inertial Navigation Systems

A range constraint method viz. centroid method is proposed to fuse the navigation information of dual (right and left) foot-mounted Zero-velocity-UPdaTe (ZUPT)-aided Inertial Navigation Systems (INSs). Here, the range constraint means that the distance of separation between the position estimates of right and left foot ZUPT-aided INSs cannot be greater than a quantity known as foot-to-foot maximum separation. We present the experimental results which illustrate the applicability of the proposed method. The results show that the proposed method significantly enhances the accuracy of the navigation solution when compared to using two uncoupled foot-mounted ZUPT-aided INSs. Also, we compare the performance of the proposed method with the existing data fusion methods.

Predicting solar disturbance effects on navigation systems

A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.

Connecting South America: River mobility and river navigation systems

This FAL Bulletin highlights the importance of rivers in the transport system of South America. Raising the issue of river mobility and policymaking is important not only for the development of river transport but also in view of its social and economic impact, especially in regions where geography complicates the provision of land infrastructure.

New functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb

In case of severe osteoarthritis at the knee causing pain, deformity, and loss of stability and mobility, the clinicians consider that the substitution of these surfaces by means of joint prostheses. The objectives to be pursued by this surgery are: complete pain elimination, restoration of the normal physiological mobility and joint stability, correction of all deformities and, thus, of limping. The knee surgical navigation systems have bee developed in computer-aided surgery in order to improve the surgical final outcome in total knee arthroplasty. These systems provide the surgeon with quantitative and real-time information about each surgical action, like bone cut executions and prosthesis component alignment, by mean of tracking tools rigidly fixed onto the femur and the tibia. Nevertheless, there is still a margin of error due to the incorrect surgical procedures and to the still limited number of kinematic information provided by the current systems. Particularly, patello-femoral joint kinematics is not considered in knee surgical navigation. It is also unclear and, thus, a source of misunderstanding, what the most appropriate methodology is to study the patellar motion. In addition, also the knee ligamentous apparatus is superficially considered in navigated total knee arthroplasty, without taking into account how their physiological behavior is altered by this surgery. The aim of the present research work was to provide new functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb. This was mainly realized by means of the identification and development of new techniques that allow a thorough comprehension of the functioning of the knee joint, with particular attention to the patello-femoral joint and to the main knee soft tissues. A knee surgical navigation system with active markers was used in all research activities presented in this research work. Particularly, preliminary test were performed in order to assess the system accuracy and the robustness of a number of navigation procedures. Four studies were performed in-vivo on patients requiring total knee arthroplasty and randomly implanted by means of traditional and navigated procedures in order to check for the real efficacy of the latter with respect to the former. In order to cope with assessment of patello-femoral joint kinematics in the intact and replaced knees, twenty in-vitro tests were performed by using a prototypal tracking tool also for the patella. In addition to standard anatomical and articular recommendations, original proposals for defining the patellar anatomical-based reference frame and for studying the patello-femoral joint kinematics were reported and used in these tests. These definitions were applied to two further in-vitro tests in which, for the first time, also the implant of patellar component insert was fully navigated. In addition, an original technique to analyze the main knee soft tissues by means of anatomical-based fiber mappings was also reported and used in the same tests. The preliminary instrumental tests revealed a system accuracy within the millimeter and a good inter- and intra-observer repeatability in defining all anatomical reference frames. In in-vivo studies, the general alignments of femoral and tibial prosthesis components and of the lower limb mechanical axis, as measured on radiographs, was more satisfactory, i.e. within ±3°, in those patient in which total knee arthroplasty was performed by navigated procedures. As for in-vitro tests, consistent patello-femoral joint kinematic patterns were observed over specimens throughout the knee flexion arc. Generally, the physiological intact knee patellar motion was not restored after the implant. This restoration was successfully achieved in the two further tests where all component implants, included the patellar insert, were fully navigated, i.e. by means of intra-operative assessment of also patellar component positioning and general tibio-femoral and patello-femoral joint assessment. The tests for assessing the behavior of the main knee ligaments revealed the complexity of the latter and the different functional roles played by the several sub-bundles compounding each ligament. Also in this case, total knee arthroplasty altered the physiological behavior of these knee soft tissues. These results reveal in-vitro the relevance and the feasibility of the applications of new techniques for accurate knee soft tissues monitoring, patellar tracking assessment and navigated patellar resurfacing intra-operatively in the contest of the most modern operative techniques. This present research work gives a contribution to the much controversial knowledge on the normal and replaced of knee kinematics by testing the reported new methodologies. The consistence of these results provides fundamental information for the comprehension and improvements of knee orthopedic treatments. In the future, the reported new techniques can be safely applied in-vivo and also adopted in other joint replacements.

Hands-Free Navigation in Immersive Environments for the Evaluation of the Effectiveness of Indoor Navigation Systems

While navigation systems for cars are in widespread use, only recently, indoor navigation systems based on smartphone apps became technically feasible. Hence tools in order to plan and evaluate particular designs of information provision are needed. Since tests in real infrastructures are costly and environmental conditions cannot be held constant, one must resort to virtual infrastructures. This paper presents the development of an environment for the support of the design of indoor navigation systems whose center piece consists in a hands-free navigation method using the Microsoft Kinect in the four-sided Definitely Affordable Virtual Environment (DAVE). Navigation controls using the user's gestures and postures as the input to the controls are designed and implemented. The installation of expensive and bulky hardware like treadmills is avoided while still giving the user a good impression of the distance she has traveled in virtual space. An advantage in comparison to approaches using a head mounted display is that the DAVE allows the users to interact with their smartphone. Thus the effects of different indoor navigation systems can be evaluated already in the planning phase using the resulting system

Cooperation & Competition Between Navigation Systems in the Rat Brain: The Role of the Hippocampus and Striatum During a Dissociative Maze Task

While many tend to think of memory systems in the brain as a single process, in reality several experiments have supported multiple dissociations of different forms of learning, such as spatial learning and response learning. In both humans and rats, the hippocampus has long been shown to be specialized in the storage of spatial and contextual memory whereas the striatum is associated with motor responses and habitual behaviors. Previous studies have examined how damage to hippocampus or striatum has affected the acquisition of either a spatial or response navigation task. However even in a very familiar environment organisms must continuously switch between place and response strategies depending upon circumstances. The current research investigates how these two brain systems interact under normal conditions to produce navigational behavior. Rats were tested using a task developed by Jacobson and colleagues (2006) in which the two types of navigation could be controlled and studied simultaneously. Rats were trained to solve a plus maze using both a spatial and a response strategy. A cue (flashing light) was employed to indicate the correct strategy on a given trial. When no light was present, the animals were rewarded for making a 90º right turn (motor response). When the light was on, the animals were rewarded for going to a specific goal location (place strategy). After learning the task, animals had a sham surgery or dorsal striatum or hippocampus damaged. In order to investigate the individual role of each brain system and evaluate whether these brain regions compete or cooperate for control over strategy, we utilized a within-animal comparisons. The configuration of the maze allowed for the comparison of behavior in individual animals before and after specific brain areas were damaged. Animals with hippocampal lesions showed selective deficits on place trials after surgery and learned the reversal of the motor response more rapidly than striatal lesioned or sham rats. Unlike previous findings regarding maze learning, animals with striatal lesions showed deficits in both place and response trials and had difficulty learning the reversal of motor response. Therefore, the effects of lesions on the ability to switch back and forth between strategies were more complex than previously suggested. This work may reveal important new insight on the integration of hippocampal and striatal learning systems, and facilitate a better understanding of the brain dynamics underlying similar navigational processes in humans.

Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Study of the performance of aids to navigation systems : phase 1, closed loop model of the process of navigation /

Final report; March 1978.