An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics

Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard Planning Domain Definition Language (PDDL) format, are still very hard to formalize for non expert engineers when the use case to model is complex. Human Robot Interaction (HRI) is one of those complex environments. This manuscript describes the rationale followed to design a planning model able to control social autonomous robots interacting with humans. It is the result of the authors’ experience in modeling use cases for Social Assistive Robotics (SAR) in two areas related to healthcare: Comprehensive Geriatric Assessment (CGA) and non-contact rehabilitation therapies for patients with physical impairments. In this work a general definition of these two use cases in a unique planning domain is proposed, which favors the management and integration with the software robotic architecture, as well as the addition of new use cases. Results show that the model is able to capture all the relevant aspects of the Human-Robot interaction in those scenarios, allowing the robot to autonomously perform the tasks by using a standard planning-execution architecture.

[1]  Juan Fasola,et al.  A socially assistive robot exercise coach for the elderly , 2013, J. Hum. Robot Interact..

[2]  Tristan B. Smith,et al.  EUROPA : A Platform for AI Planning, Scheduling, Constraint Programming, and Optimization , 2012 .

[3]  D Feil-Seifer,et al.  Socially Assistive Robotics , 2011, IEEE Robotics & Automation Magazine.

[4]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[5]  Malik Ghallab,et al.  Deliberation for autonomous robots: A survey , 2017, Artif. Intell..

[6]  Sutton,et al.  Further Advances in Unmanned Marine Vehicles , 2012 .

[7]  R. Ackermann Minnesota Studies in the Philosophy of Science , 1975 .

[8]  A. Koller,et al.  Speech Acts: An Essay in the Philosophy of Language , 1969 .

[9]  J. Christopher Beck,et al.  Robots in Retirement Homes: Applying Off-the-Shelf Planning and Scheduling to a Team of Assistive Robots (Extended Abstract) , 2017, IJCAI.

[10]  C. Raymond Perrault,et al.  A Plan-Based Analysis of Indirect Speech Act , 1980, CL.

[11]  Albert-Ludwigs A Continual Multiagent Planning Approach to Situated Dialogue , 2008 .

[12]  Konstantin Kondak,et al.  Journal of Intelligent and Robotic Systems manuscript No. , 2022 .

[13]  Ángel García Olaya,et al.  Control of autonomous mobile robots with automated planning , 2011 .

[14]  Petros Maragos,et al.  I-Support: A robotic platform of an assistive bathing robot for the elderly population , 2020, Robotics Auton. Syst..

[15]  Craig A. Knoblock,et al.  PDDL-the planning domain definition language , 1998 .

[16]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[17]  Amedeo Cesta,et al.  A Holistic Approach to Behavior Adaptation for Socially Assistive Robots , 2020, Int. J. Soc. Robotics.

[18]  Vicente Matellán Olivera,et al.  HiMoP: A three-component architecture to create more human-acceptable social-assistive robots , 2017, Cognitive Processing.

[19]  Jörg Hoffmann,et al.  The Metric-FF Planning System: Translating ''Ignoring Delete Lists'' to Numeric State Variables , 2003, J. Artif. Intell. Res..

[20]  Ana Paiva,et al.  Social Robots for Long-Term Interaction: A Survey , 2013, International Journal of Social Robotics.

[21]  Vidal Alcázar,et al.  pelea : Planning , Learning and Execution Architecture , 2010 .

[22]  Nicola Muscettola,et al.  Planning in Interplanetary Space: Theory and Practice , 2000, AIPS.

[23]  Carme Torras,et al.  Probabilistic Planning for Robotics with ROSPlan , 2019, TAROS.

[24]  Peter Langhorne,et al.  Comprehensive geriatric assessment for older hospital patients. , 2004, British medical bulletin.

[25]  Maria Fox,et al.  Combining temporal planning with probabilistic reasoning for autonomous surveillance missions , 2017, Auton. Robots.

[26]  Cristina Suarez-Mejias,et al.  A Socially Assistive Robotic Platform for Upper-Limb Rehabilitation: A Longitudinal Study With Pediatric Patients , 2019, IEEE Robotics & Automation Magazine.

[27]  Ronald P. A. Petrick,et al.  Planning Dialog Actions , 2007, SIGDIAL.

[28]  F. Mahoney,et al.  FUNCTIONAL EVALUATION: THE BARTHEL INDEX. , 2018, Maryland state medical journal.

[29]  José Carlos González,et al.  CLARC: A Cognitive Robot for Helping Geriatric Doctors in Real Scenarios , 2017, ROBOT.

[30]  Bernhard Nebel,et al.  Continual planning and acting in dynamic multiagent environments , 2006, PCAR '06.

[31]  Natàlia Hurtós,et al.  ROSPlan: Planning in the Robot Operating System , 2015, ICAPS.

[32]  Csr Young,et al.  How to Do Things With Words , 2009 .

[33]  José Carlos Pulido,et al.  CLARC : a Robotic Architecture for Comprehensive Geriatric Assessment , 2016 .

[34]  José Carlos González,et al.  Challenges on the Application of Automated Planning for Comprehensive Geriatric Assessment Using an Autonomous Social Robot , 2018, WAF.

[35]  Beno Benhabib,et al.  A Multimodal Emotional Human–Robot Interaction Architecture for Social Robots Engaged in Bidirectional Communication , 2020, IEEE Transactions on Cybernetics.

[36]  Ronald P. A. Petrick,et al.  Planning for Social Interaction in a Robot Bartender Domain , 2013, ICAPS.

[37]  Ari K. Jónsson,et al.  MAPGEN: Mixed-Initiative Planning and Scheduling for the Mars Exploration Rover Mission , 2004, IEEE Intell. Syst..

[38]  Maria Fox,et al.  PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains , 2003, J. Artif. Intell. Res..

[39]  Leslie Pack Kaelbling,et al.  Constructing Symbolic Representations for High-Level Planning , 2014, AAAI.

[40]  Fernando Fernández,et al.  A Modelling and Formalisation Tool for Use Case Design in Social Autonomous Robotics , 2019, ROBOT.

[41]  Alexander Koller,et al.  Automated Planning for Situated Natural Language Generation , 2010, ACL.

[42]  U S Nayak,et al.  Balance in elderly patients: the "get-up and go" test. , 1986, Archives of physical medicine and rehabilitation.

[43]  Frederic Py,et al.  T-REX: partitioned inference for AUV mission control , 2012 .

[44]  Alessandro Di Nuovo,et al.  Social Robots as Psychometric Tools for Cognitive Assessment: A Pilot Test , 2017, HFR.

[45]  Alessandro Saffiotti,et al.  A Planner for Ambient Assisted Living: From High-Level Reasoning to Low-Level Robot Execution and Back , 2014, AAAI Spring Symposia.

[46]  José Carlos González,et al.  A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots , 2017, Cognitive Systems Research.