technical coordinating unit on robot planning

http://www.planet-noe.org

European Networkof Excellence in

AI Planning

Technical Coordinating Unit on

Robot Planning

Robot Planning TCU 2

TCU Participants• Aegean University, Vangelis Kourakos• Brescia University, A.Gerevini• Freiburg University, B.Nebel• Genova University, E. Giunchiglia• GMD, J.Hertzberg• IRST, P.Traverso• LAAS, M.Ghallab• Linköping University, P.Doherty• Lund University, J. Malec• Madrid Carlos III University, D.Borrajo• Munich University, M.Beetz• NCSR Demokritos, C. Spyropoulos, • ONERA, P.Fabiani• Orebro University, A.Saffiotti• Rovira i Virgili University, M.A. Garcia• Siemens Corp. Techno., W.Feiten• Ulm University, S. Biundo, B.Schattenberg


Roadmap

• Problems and challenges in Robot Planning• State of the art• Technology maturity • What needs to be done• Research at TCU Nodes


Robot planning

A computational activity that relies on:– Models of environment and robot – Specification of required goals and utilities– Online input from sensors and communication channels

to perform prediction and choices for achieving goals and utilities

• Robotics without planning: handcoded environment structure, strategy and goals into purely reactive control

• Specifics of planning in robotics: – heterogeneous partial models and state information, – direct integration of planning to acting and sensing


Purpose of planning in robotics

Improve the performance of robots for carrying out – a set of tasks in – a class of environments

Performance criteria:• Robustness of the behavior of robots with respect to:

– Variety of environments– Diversity of tasks

• Quality and cost of:– Environment modeling– Modification and verification of robot controllers– Interaction with and among robots


Forms and components of robot planning

• Path and motion planning: Geometric path and control trajectory along that path

• Perception planning: – Which information is needed, and when– Where to look for it– Which sensors are most adequate, and how to use them

• Navigation planning: Strategy using localization primitives, visual servoing and other

sensory-controlled motion primitives, for reaching a goal, exploring an area


• Manipulation planning: Similar strategy of sensory-motor primitives using forces and

touch (haptics), vision, etc, to handle objects and assemblies

• Task planning: Classical set of state-transition operators, with

Time and resource allocation, dynamic environment, uncertainty

• Communication planning: In multi-robots cooperation, Man-machine interaction

How to query needed information, which feedback is required



PLANET is not active in all these areas

Robot Planning TCU has to be aware of them and their common features:– Uncertainty

– On-line constraints

– Dynamic environments and feedback loops

– Multi-agency

Robot Planning TCU has to build on top of them



Challenges and requirements

Integration of sensory-motor capabilities

with deliberative, goal-oriented capabilities

Integrate planning to acting

Integrate heterogeneous representations: Space, time, kinematics and dynamics, physics of sensors,

uncertainty, logical properties, various constraints, including

computational

Integrate various forms of planning

Integrate planning and learning

to extend sensory-motor controllers


State of the art

Available material

• Good surveys and reference works in the literature on basic robot planning components, e.g.– Path and motion planning

– Task planning

• Roadmap surveys current work on– Integration of planning, acting and sensing (Ulm Univ.)

– Uncertainty in robot planning (ONERA)

– Integration of planning and learning (Madrid)


Maturity

Mainly of planning components :• Path and motion planning : a well mature technology

Techniques: computationnal geometry and probabilistic algorithms

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Maturity

• Task planning : a wealth of algorithms in the classical frameworkTechniques: search, heuristics, disjunctive refinement, CSPs

• Perception planning: some focused problems well solved, e.g. viewpoint selectionTechniques: mathematical programming

• High level reactive controllers: preprogrammed goal-directed behaviors– PRS, Propice, RAP, SRCs and similar systems well

advanced and integrated to sensory-motoric level– Most laboratory robots run on them


Possible technology transfer

• Within roboticsThere are other limiting factors for industrial deployment, e.g.

sensory-motoric functions, reliability, security and cost– Reactive controllers: the easy first step– Special purpose navigation and perception planning

capabilities

• In other domains– Path and motion planning: in CAD, Animation and Graphics– Tasks planning with time and resources: in manufacturing,

process planning, workflow management, network management

– Reactive controllers: in transportation systems– Integrated planning systems in well structured domains:

autonomous spacecraft– Perception planning in surveillance systems


What needs to be done

• Research on integration problems– Planning and acting

• Reaction / deliberation architecture

• Planning depth and on-line constraints

• Execution models

• Fault detection, diagnosis, recovery

– Heterogeneous representation

– Heterogeneous planning techniques

– Planning with information gathering and sensing• Access to world state

• Planning (with) action sensing

– Planning and learning


Typical projects

• Cooperating service robots

Transportation, surveillance, cleaning, search and gathering of

object, e.g., office assistants

• Surveillance and monitoring of the traffic network

• Exploration robots, environment monitoring: the Baltic

watch project


TCU activities

ECAI Workshop August 2000

Perception Planning• Talks

– Perception planning for surveillance, tracking or cooperationP.Fabiani

– Perception planning for autonomous service robotsM.Beetz, J.Schumacher

– The WITAS project, anchoring and perception planningP.Doherty

• Discussion on representations and reasoning required for sensor models, environments, sensing tasks


TCU Activities

Dagstuhl seminar, October 2001

Plan-based Control of Robotics Agents• Topics:

– perception in plan-based control

– plan notations, plan execution, and monitoring

– execution-time plan management

– formal models of plan-based control

– plan-based control and learning

– challenge problems and benchmarks

• Participants: 50, from Europe, USA, Australia• Planned outcome: Book LNAI, Springer


TCU Activities

Workshops during 2002

• At AIPS'02– 3rd Cognitive Robotics Workshop– Other workshops ? (submission deadline: September 21st)

• At ECAI'02

technical coordinating unit on robot planning

Documents

motion planning

pathperception planning

assembliestask planning

themnavigation planning

areasrobot planning

direct integration of

robotsrobot planning

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