Robotic Research: Are We Applying the Scientific Method?

Once upon a time validation of robotic research was relatively straightforward. Let us assume, for example, that a researcher had published in a journal a novel adaptive control law with a numerical example on a two-link robot. Beyond the formal proof of convergence, he supplied to the reader the differential equations used to model the system, including the corresponding dynamic parameters (nomore than 20 numbers), the eventual quantization and discretization of the controller, the solver details of the software used, and the sensor noise statistics. Not only the reviewers, thus, but also each single reader would have the possibility to re-run the numerical simulations in a half-day of work. The communitywould have the possibility to test, validate, generalize, and benchmark the algorithm. Since then, robotics has changed, the machines are nowmuch more complex in their kinematics, number of degrees of freedom, and are filled with several sensors. Also, giant steps have been made: the robots left the confined industrial cells to jump within unstructured environments, not only in the industry but also in the houses, the museums, the airports, and the post-disaster sites; they perform a number of exciting tasks such as exploration, maintenance, interaction with humans, search and rescue . . .wait, is it really so? Beyond specific outstanding experiences, beyond the claims of the constructors and lab's directors, how many robots run, autonomously or semi-autonomously, in our daily lives? Not so many, to be honest. A few vacuum cleaning robots, this is all (Guizzo, 2015). While we have several noticeable robotic tools (parking assist systems, lane keeping assist systems, space systems), where are all the learning and adaptable robot protagonists of thousands of scientific publications in the last years? Our robots can avoid the predicted unpredicted events, but what about the unpredicted? The information required to validate the two-link example above is obviously not possible any more but why are we experiencing so large a gap between claimed and real robotics? Why has it been the case for several years now that the robotics revolution is regularly postponed to the next 10 years . . .? The grand challenge for the robotics community is to discuss, from its foundations up, the way its research is conducted. It is a huge effort involving complex interactions among the institutions, the ministries, the funding agencies, and the individual researchers' careers. Research is funded by selection of proposals, at each call more andmore imaginative which, however, most of the time end with more or less disappointing demos. This process includes perforce to review the validation of the research process in a wide sense and, within this, the publishing process. The latter is becoming (apparently) faster and more selective with new ideas spread out and absorbed by other researchers in a very short time during which a paper placed in the hands of a reviewer or a debatable reject may be a dramatic event. The previous claims are intentionally provocative, and so is the title of this article: are we (still) applying the scientific method in robotics? Let us frankly discuss this question. The Oxford English Dictionary defines the scientific method as "a method or procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses." The strict link existingwith theory and experimentation is evident and further elaborated by, for instance, Karl Popper, who claimed that the criterion of the scientific status of a theory is its falsifiability

Handling robot constraints within a Set-Based Multi-Task Priority Inverse Kinematics Framework

Set-Based Multi-Task Priority is a recent framework to handle inverse kinematics for redundant structures. Both equality tasks, i.e., control objectives to be driven to a desired value, and set-bases tasks, i.e., control objectives to be satisfied with a set/range of values can be addressed in a rigorous manner within a priority framework. In addition, optimization tasks, driven by the gradient of a proper function, may be considered as well, usually as lower priority tasks. In this paper the proper design of the tasks, their priority and the use of a Set-Based Multi-Task Priority framework is proposed in order to handle several constraints simultaneously in real-time. It is shown that safety related tasks such as, e.g., joint limits or kinematic singularity, may be properly handled by consider them both at an higher priority as set-based task and at a lower within a proper optimization functional. Experimental results on a 7DOF Jaco$^2

Car collision avoidance with velocity obstacle approach

The obstacle avoidance maneuver is required for an autonomous vehicle. It is essential to define the system's performance by evaluating the minimum reaction times of the vehicle and analyzing the probability of success of the avoiding operation. This paper presents a collision avoidance algorithm based on the velocity bstacle approach that guarantees collision-free maneuvers. The vehicle is controlled by an optimal feedback control named FLOP, designed to produce the best performance in terms of safety and minimum kinetic collision energy. Dimensionless accident evaluation parameters are proposed to compare different crash scenarios

Safety-related Tasks within the Set-Based Task-Priority Inverse Kinematics Framework

In this paper we present a framework that allows the motion control of a robotic arm automatically handling different kinds of safety-related tasks. The developed controller is based on a Task-Priority Inverse Kinematics algorithm that allows the manipulator's motion while respecting constraints defined either in the joint or in the operational space in the form of equality-based or set-based tasks. This gives the possibility to define, among the others, tasks as joint-limits, obstacle avoidance or limiting the workspace in the operational space. Additionally, an algorithm for the real-time computation of the minimum distance between the manipulator and other objects in the environment using depth measurements has been implemented, effectively allowing obstacle avoidance tasks. Experiments with a Jaco$^2$ manipulator, operating in an environment where an RGB-D sensor is used for the obstacles detection, show the effectiveness of the developed system

Educazione e formazione nella visione di Paolo Dieci.

Questo breve intervento, come recita il titolo di questa giornata, intende contribuire a evidenziare alcuni aspetti fondamentali dello “Sviluppo Umano e Sostenibile” che stavano a cuore a Paolo Dieci

Effects of Dynamic Model Errors in Task-Priority Operational Space Control

Control algorithms of many Degrees Of Freedom (DOFs) systems based on Inverse Kinematics or Inverse Dynamics approaches are two well-known topics of research in robotics. The large number of DOFs allows the design of many concurrent tasks arranged in priorities, that can be solved either at kinematic or dynamic level. This paper investigates the effects of modeling errors in operational space control algorithms with respect to uncertainties affecting knowledge of the dynamic parameters. The effects on the null-space projections and the sources of steady-state errors are investigated. Numerical simulations with on-purpose injected errors are used to validate the thoughts

experimental investigation on the fixed bed of a small size biomass boiler

Abstract During the last decades, the increase of the world energy consumption promoted the renewable resource development and use. Together with wind, solar and hydro energy, biomasses play a key role in the reduction of the industrial environmental impact; moreover, the biomass combustion systems are very attractive for micro-generation purpose. In this paper, experimental tests on a 140kW small size fixed bed biomass boiler were carried out. The main goal was to study the thermal behavior and some chemical products, such as CO, CO2, Methane and Ethylene, from the combusting fixed bed of the system. In fact, despite the wide amount of literature for the laboratory scale systems, the commercial scale boilers have been seldom studied by the experimental point of view. The data were obtained by varying the operational parameters of the boiler, that are the air excess and the secondary to primary air feeding ratio. Furthermore, the collected data were analyzed and the relationship between the thermal-chemical data and the control variables was discussed

Experimental Results for Set-based Control within theSingularity-robust Multiple Task-priority Inverse KinematicsFramework

Inverse kinematics algorithms are commonly used in robotic systems to achieve desired behavior, and several methods exist to ensure the achievement of numerous tasks simultaneously. The multiple task-priority inverse kinematics framework allows a consideration of tasks in a prioritized order by projecting task velocities through the null-spaces of higher priority tasks. Recent results have extended this framework from equality tasks to also handling set-based tasks, i.e. tasks that have an interval of valid values. The purpose of this paper is to further investigate and experimentally validate this algorithm and its properties. In particular, this paper presents experimental results where a number of both set-based and equality tasks have been implemented on the 6 Degree of Freedom UR5 which is an industrial robotic arm from Universal Robots. The experiments validate the theoretical results.(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works