CAREER: Linguistic Control of Mobile Robots

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When humans instruct each other h w to carry out particular tasks,nly a limited number oftokenized (linguistic)instructions are used.In contrast to this,classic control theory speci .esa control action to be carried out at each time instant.But,in a number f applications,suchas semi-autonomous service robots for industrial and domestic use,intelligent appliances,andcommunication constrained embedded and/or teleoperated devices,the control procedures havea natural,linguistic .avor.The interpretation here is that linguistic control instructions specifyparticular modes f peration rather than explicit control values.The verall objective f this CAREER-prop sal is t develop and disseminate rational meth-ds for understanding how continuous devices,such as mobile rob ts,should be controlled usingcomputer generated,linguistic inputs.In particular,it will be studied how these instructionsshould be de .ned,selected,and coded in rder to minimize the number of bits transmitted fromthe computer t the rob t,while guaranteeing that the system meets its speci .cations.F r this,an information theoretic approach t control theory will be developed,serving as a useful toolnot nly for source coding of control signals,but also for describing how symb lic instructionsshould be interpreted and perated n by the continuous systems.Questions concerning whatsensors and actuators to use in a given rob tic application can be addressed quite elegantlywithin this framew rk as well.The development of this program will serve as a foundation for a teaching and research careerin electrical and computer engineering,with particular emphasis n control theory and rob tics.In particular,the e .ort will be focused n the following key areas:Hybrid Models: Control theoretic models will be developed for bridging the gap between thecontinuous (the device dynamics)and the discrete (the linguistic control inputs).The proposedmodels will give the symbolic inputs a clear,control theoretic interpretation,at the same timeas the expressive p wers of di .erent sets f control inputs can be made explicit.Complexity Measures and Coding Theory: A complexity measure,corresp nding to thenumber of bits needed for c ding a particular control procedure,will be proposed.Furthermore,by establishing probability distributions ver the set f control modes,optimal c ding algorithmscan be derived.Multi-Modal and Multi-Agent Control Design: Strings of appropriate control modes willbe constructed that make the systems meet given speci .cations while keeping the descriptionsshort.F r this we will design control laws that use the available sensory data in an e .cientway.These results will be extended t multi-agent control where formation maintenance andobstacle avoidance should be achieved while minimizing the inter-agent communications.Educational Plan: Due t the multidisciplinary nature f the proposed w rk,the under-graduate control curriculum will be modi .ed and tw senior level undergraduate courses willbe included in the curriculum at the Georgia Institute of Technology.A multi-agent rob tictestbed where b th human and computer generated inputs can be used as a basis for the motioncontrol will furthermore be developed.1