Comprehensive Geria.tcic Assessment ( CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLA RC, a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Built around a shared internal representation of the outer world, the architecture is composed of softwa,r e modules able to plan and generate a stream of actions, t.o execute actions emanated from the representation or to update this by including/removing items at different abstraction levels. Percepts, actions and intentfons ooming from all software modules are grounded within th.is unique representation. This allows the robot to react to unexpected events and to modify the course of action accord ing to the dynamics of a scenario built around the interaction with the patient. The paper describes the architecture of the system as well as the preliminary user studies and evaluation to gather new user requirements.

http : //wvv.pl g. inf.uc3m.es Abstract. Comprehensive Geriatric Assessment is a medical procedure to evaluate t he physical, social and psychological status of elder patients. One of it s phases consists of performing different tests t o the pat ient or relatives. In t his paper we present the challenges to apply Automated P lanning to control an autonomous robot helping t he clinician to perform such test s. On t he one hand the paper focuses on the modelling decisions t aken, from an init ial approach where each t est was encoded using slightly different domains, to the final unified domain allowing any test to be represented. On the other hand, the paper deals with practical issues arisen when executing the plans. Preliminary t ests performed with real users show that t he proposed approach is able to seamlessly handle t he patient-robot interaction in real time, recovering from unexpected events and adapt ing t o t he users' preferred input method, while being able to gather all the informat ion needed by t he clinician.

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Abstract.Oversubscription planning (OSP) appears in many real problems where finding a plan achieving all goals is infeasible. The objective is to find a feasible plan reaching a goal subset while maximizing some measure of utility. In this paper, we present a new technique to select goals "a priori" for problems in which a cost bound prevents all the goals from being achieved. It uses estimations of distances between goals, which are computed using relaxed plans. Using these distances, a search in the space of subsets of goals is performed, yielding a new set of goals to plan for. A revised planning problem can be created and solved, taking into account only the selected goals. We present experiments in six different domains with good results.

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