Zero-gravity movement studies

The use of computer graphics to simulate the movement of articulated animals and mechanisms has a number of uses ranging over many fields. Human motion simulation systems can be useful in education, medicine, anatomy, physiology, and dance. In biomechanics, computer displays help to understand and analyze performance. Simulations can be used to help understand the effect of external or internal forces. Similarly, zero-gravity simulation systems should provide a means of designing and exploring the capabilities of hypothetical zero-gravity situations before actually carrying out such actions. The advantage of using a simulation of the motion is that one can experiment with variations of a maneuver before attempting to teach it to an individual. The zero-gravity motion simulation problem can be divided into two broad areas: human movement and behavior in zero-gravity, and simulation of articulated mechanisms

High level task planning with inference for the TIAGo robot

The need to combine task planning and motion planning in robotics is well understood. The task planner generates a plan to solve the problem while the motion planner executes the actions of the problem. The previous framework is applied in many state machines that solve complex problems. But in this project we want to present an interface that communicates the task planner layer and the motion planner layer, and updates the geometric information of the environment to inform the task planner. This framework allows to solve complex tasks with basic information of the goal, and replan whenever the motion could not be executed. All the information of the problems is modelled as logical predicates. The objective of this project is to generate a generic model of the environment, with a set of feasible motions of the robot, and use this interface to solve many different planning problems involving those actions, by just giving simple goals. The result is to make the robot more autonomous and allow that any user could use it by giving simple orders. Moreover this project presents the different frameworks and algorithms used to simulate those actions in the robot such as: Sequential Quadratic Programming optimization, Rapidly Random Exploring Tree (RRT) or SBPL global planning. It also shows an introduction to PDDL language used to model the problem and the actions, and the Fast-Froward (FF) solver that is the responsible to translate the problem as a graph and solve it. Finally we test it on different experiments in simulation, by using the TIAGo platform of PAL robotics. The results are promising and allow to dream in service robots solving complex tasks simply computing and modelling basic actions

Leveraging New Plans in AgentSpeak(PL)

Many papers have been written on the anticancer properties of dietary flavonoids, and a range of potential mechanisms of action of flavonoids. However, most dietary flavonoids - notably polyphenolic flavonoids—have very poor ADME properties, and the levels necessary to stop growth of tumour cells cannot be sustained in a human body trough dietary intake alone. At present no flavonoid based drugs are clinically used in cancer therapy. Thus, whereas epidemiological and pre-clinical data seem to indicate a high potential for flavonoids, from the point of view of the pharmaceutical industry and drug developers, they are considered poor candidates. The flavones—which constitute a subgroup of the flavonoids—show some structural analogy with oestrogen and are known to interact with human oestrogen receptors, either as agonist or as antagonist. They are classed as phytoestrogens, and may play a role in cancer prevention through a mechanism of action possibly similar to that of the clinically used medication tamoxifen. Flavones are abundantly present in common fruits and vegetables, many of which have been associated with cancer prevention. Their phytoestrogen activity makes that they can assert their biological action at concentrations that are realistically achievable in the human systemic circulation