Vjerojatnosni model robotskoga djelovanja u fizičkoj interakciji s čovjekom

U doktorskom radu razvijen je vjerojatnosni model pomoću kojeg robot donosi odluke o svojem djelovanju putem fizičke interakcije s čovjekom. Klasifikacijom taktilnih podražaja na temelju kapacitivnog senzora, sile i prostornog položaja razaznaju se elementi i smisao interakcije. Kako bi model imao određenu autonomiju i mogućnost kretanja kroz prostor u sklopu istraživanja obrađen je problem prostornog kretanja. U sklopu istraživanja definirana je višekriterijska interpretacija radnog prostora u kojoj postoji distinkcija između objekata u okolini, čovjeka, ciljeva, samog robota te putanja robota. Model interakcije je oblikovan kao slijed radnji koje robot izvršava što u konačnici rezultira robotskim djelovanjem. Definiranje varijabli vjerojatnosti modela proizlazi iz interakcije s čovjekom. Naučeni obrasci predstavljaju dugoročno znanje na temelju kojih se oblikuje robotsko djelovanje u skladu s trenutnim stanjem okoline. Vremenskim razlikovanjem bližim događajima pridaje se značajno veći faktor utjecaja, a onim udaljenijim u prošlost mnogo manji. U laboratorijskim uvjetima provedeni su pokusi na realnom sustavu koji čine robotska ruka s integriranim senzorima momenata i upravljačkom jedinicom, računalo, kao i „umjetna koža“ koja posjeduje mogućnost razlučivanja ljudskog dodira i neposredne blizine prvenstveno biološkog materijala. Eksperimentima su utvrđena ograničenja primjene autonomnog djelovanja robota

Object Tracking with a Multiagent Robot System and a Stereo Vision Camera

AbstractWhen working with a robot in terms of object manipulation the essential information is relative position between robot's tool center point (TCP) and the object of interest. This paper proposes a method of frame relative displacement and describes a working multiagent robot application that can be used for tracking, tooling or handling operations with the use of stereo vision in unstructured laboratory environment. Robot system is composed of two Fanuc robot arms, one of which carries a stereo vision camera system and the other which is guided in relation to object of interest. The latter robot has a marker that is used for navigation between the robot and the object of interest. Image processing, marker detection, 3-D coordinates extraction, coordinate system transformations, offset coordinates calculation and communication are handled using c++ multithread program and TCP/IP protocol

VIRTUAL SURFACE FOR HUMAN-ROBOT INTERACTION

As cooperation between robots and humans becomes increasingly important for new robotic applications, human-robot interaction (HRI) becomes a significant area of research. This paper presents a novel approach to HRI based on the use of a virtual surface. The presented system consists of a virtual surface and a robot manipulator capable of tactile interaction. Multimedia content of the virtual surface and the option to manually guide the manipulator through space provide an intuitive means of interaction between the robot and the operator. The paper proposes shared workspaces for humans and robots to simplify and improve human-robot collaboration when performing various tasks utilizing a developed interaction model

A multiagent framework for industrial robotic applications

AbstractThe paper presents a novel approach toward modeling and governing complex system behavior in flexible and adaptive robotic assembly systems. A fully distributed multiagent approach is implemented for autonomous control. The system is defined at multiple levels of granularity where agents provide services in respect to the current global goal. A decentralized multiagent approach is adopted for reasons of flexibility and fault tolerance embedded in the design phase. To prove the concept a robotic application for intelligent assembly is presented and discussed. It consists of multiple industrial robots equipped with force/torque sensors, 2D and 3D vision systems, automatic tool changers and other sensors and actuators. Through fusion of sensory input and mutual communication agents construct and negotiate an assembly plan and reconfigure respectively

Industrial robotic system with adaptive control

AbstractIn this paper an adaptive multiagent robotic assembly system is presented. State of the art industrial equipment is utilized to perform various assembly tasks in a highly unstructured environment without the need for central control. The emphasis is given to the developed methods that address particular issues in such robotic assembly systems. Close collaboration and intertwined work with human operators is one application under development, possible due to complex sensorial inputs on the robots. Active voice commands and prompts additionally contribute to human-robot interaction. Encounter with unknown objects is another issue that has been addressed and can be solved autonomously for simple case scenarios. Actual assembly applications as well as applications under development are presented. The operation in unstructured environments has been facilitated with vision systems, F/T sensors and other sensorial devices

Task planning based on the interpretation of spatial structures

U ovom istraživanju razvijen je novi algoritam planiranja za transformaciju početnog neuređenog stanja objekata u uređeno konačno stanje. Zadatak algoritma planiranja je pronaći mogući niz djelovanja kojima se početno stanje okoline, kroz konačan broj diskretnih transformacija, može dovesti u zadano konačno stanje. Stanje okoline tumači se kroz položaj i orijentaciju objekata. Zadatak planiranja rješava se u dva koraka. Razvijena je konstruktivna heuristika pomoću koje se dobiva početni skup rješenja. Konstruktivna heuristika koristi mutacije za generiranje početne populacije. Genetski algoritam je razvijen za optimizaciju početnog skupa rješenja. Genetski algoritam karakteriziran je usporednom evolucijskom strategijom za pronalaženje rješenja, s ciljem prostorne pretvorbe neuređenog stanja objekata u uređeno, ograničen na dvodimenzionalnu interpretaciju radnog prostora. Verifikacija algoritma planiranja napravljena je u virtualnom okruženju.In this research, a new task planning algorithm is developed for building a desired object configuration from a given initial unordered object state. The task of the planning algorithm is to find a feasible set of actions, i.e. a finite number of discrete transformations, which can rearrange the objects into a desired ordered final state. The environment is interpreted through the position and orientation of the objects. The solution to the planning problem is proposed as a two-step method. First, a constructive heuristic generates an initial set of good solutions. The constructive heuristic uses only mutations for making an initial population of state transitions. A genetic algorithm is developed for optimizing the initial set of solutions. The genetic algorithm is characterized by a parallel evolutionary strategy, with the aim of spatial transformation of unordered object states into ordered object states. The algorithm can be used for solving the task planning problems represented in the two-dimensional space. Verification of the planning algorithm is done in a virtual environment