Presentation Transcript
ISI Polymorphic Robotics Labhttp://www.isi.edu/robots: ISI Polymorphic Robotics Lab http://www.isi.edu/robots Mission
To build Self-Reconfigurable Systems such as metamorphic robots, agents, and smart structures that go where biological systems have not gone before!!!
Projects and Awards
YODA (1996) The 2nd place in AAAI competition
Dreamteam (1997) RoboCup World Champion
Intelligent Motion Surface in MEMS (1996-98)
CONRO Self-Reconfigurable Robots (1998-)
People, Robots and Facilities
Experienced and talented research team
3 Denny robots, 5 SoccerBots, 18 CONRO modls
Large labs and workshops, many instrumentations
Self-Reconfigurable Robots: Self-Reconfigurable Robots
CONRO Self-Reconfigurable Modules: CONRO Self-Reconfigurable Modules A network of physically coupled agents Self-assembling into various configurations!
Relentless CONRO Robots: Relentless CONRO Robots
“Live Surgery” Reconfiguration: “Live Surgery” Reconfiguration
Beyond-Bio Self-Reconfiguration: Beyond-Bio Self-Reconfiguration
Challenges in Control : Challenges in Control Distributed
Autonomous modules must be coordinated by local configuration information (no unique IDs or brain modules)
Dynamic
Network and configuration topology changes
Asynchronous
Communication with no real-time clocks, global or local
Scalable
The size and shape are not determined dynamically
Fault-tolerant
Miniature and self-sufficient
Digital Hormones: Digital Hormones Content-based messages
No addresses nor identifiers
Have finite life time
Trigger different actions at different sites
Floating in a global medium
Propagated, not broadcast
Internal circulation, not external deposit (pheromones)
Preserve local autonomy for individual sites
Hormones can modify module behaviors (RNA)
The Uses of Digital Hormones: The Uses of Digital Hormones Communication in dynamic network
Cooperation among distributed autonomous modules
Locomotion
Reconfiguration
Synchronization
Global effects by weak local actions
Conflict resolution (multi hormone management)
Navigation
Shape adaptation and self-repairing
Hormones for Caterpillar Move: A simple one-pass hormone from head to tail
Controls and synchronizes all motor actions
Independent from the length of the snake Hormones for Caterpillar Move
Reconfigure Insect Snake: Reconfigure Insect Snake
Autonomous Docking: Autonomous Docking A great challenge for self-reconfiguration
Require precise sensor guidance
Demand precision movement
Complex dynamics in micro-gravity environment
Self-Assembly in Space: Self-Assembly in Space Cost Effective
For a 10km long SSPS
>2,500 hours of astronaut space walk
4/11/2002, girder assembly (2*6 hours)
>$5 billion for assembly cost
Feasible Strategy
Most jobs by self-assembly
Critical jobs done by astronauts
A Vision for Space Self-Assembly: A Vision for Space Self-Assembly
Three Enabling Technologies: Three Enabling Technologies Intelligent and Reconfigurable Component (IRC)
Can free-float and dock to form structures
Distributed Process Controller (DPC)
Can plan self-assembly in a distributed manner and recover from unexpected situations
Free-flying Fiber Match-Maker Robots (FIMER)
Can search, navigate, bring-together and dock IRCs
Intelligent Reconfigurable Components: Intelligent Reconfigurable Components An IRC has (1) a controller, (2) a set of named connectors, (3) wireless communication, (4) self-locating system, and (5) short-range sensors for docking guidance
Reconfigurable Connectors: Reconfigurable Connectors
The Global Process Control: The Global Process Control How do modules know when and where to connect?
Advantages for distributed control
Coordination of autonomous modules without fixed brain
Support dynamic configuration topology
Asynchronous: communication without global clocks
Scalable: support growing structures
Fault-tolerance
Self-repairing capability
Self-replanning for unexpected events
Proposed Process Control: Proposed Process Control Assumptions
Components/connectors have unique identifiers
Assembly sequence embedded in components
Procedures
Activate self when receiving a call for its ID or type
Call FIMER robots to assist docking (when activated)
Activate the next connectors to be docked
FIMER Robots: FIMER Robots Two-headed robot with fiber/rope Free-flying head (6DOF) Navigate and dock to the connectors Rail-in fiber to bring parts together Simple arms to assist dock Onboard power or refuel capability
FIMER Dynamics and Control: FIMER Dynamics and Control Find relevant connectors based on their location information Railing in the fiber only when there is no tension Research Issues: * Dynamics of tethered objects in zero-gravity environment * Speed control * Collision control * Prevent tangling
Proposed Experiments: Proposed Experiments Build modules for autonomous planning, navigation, & docking
“2D flight-test” on an air hockey table
Extensible to future 3D flight-test in micro-gravity environment
Flying Module Prototype: Flying Module Prototype
Slide24: ISI Polymorphic Robotics Laboratory
http://www.isi.edu/robots
A Model of Flying Puck: A Model of Flying Puck M(n)n’ + C(n)n + Dn + g(h) = t
M(n) is the moment of inertia matrix,
C(n) is the centrifugal and Coriolis forces,
D is the damping matrix,
and n =[u v r]’ is the velocity vector
and h=[x y y]’ is the configuration vector
g(h) is the vector of gravitational and buoyant forces
and t = [Tu Tv Tr] is the control forces and torques
The Control of Flying Puck: The Control of Flying Puck Using vision to sense the location/speed
Analog control of speed via wireless comm.
Close-loop control
The desired x and y position are the target position
The desired orientation is equal to the “target angle” so that the vehicle is always facing the target.
Tu = m(Tx cos y + Ty sin y)
Tv = 0
Tr = Iz Ty
Conclusions and Future Work: Conclusions and Future Work Self-reconfigurable robots provide a very rich source for new research problems
Hormone-inspired approach is very promising direction for distributed control
Self-assembly in space is a good application of self-reconfiguration
Future directions:
Environmental driven self-reconfiguration
New generation of enhanced and robust modules
Hormone-based programming