Anders Rehan Pattern
1. Implement debugging state colouring - Anders
2. Change random parameters to get better ground coverage - Rehan
3. In chain has probability of disconnecting when (at front) or back - Rehan
4. Chains move around - (modified) random walk + search for chain
5. Better alignment at back of chain
6. Make sure sbot can approach chain of more than one sbot successfully
7. Fix distance at back of chain
- Pattern formation in mobile actuator and sensor network Chen
Example of real world robots using (pseudo) gps to form patterns using simple robots. Each robot is related positionally to leader who broadcasts his position.
- Pattern formation and optimization in army ant raids Bonabeau
Example of functional pattern formation in the natural kindom. Mathematical modelling.
- A general algorithm for robot formations using local sensing and minimal communication. Fredslund, Mataric
Simulation and Real robots. Formations formed by keeping angle and distance from friend. Global communication of desired pattern paramters. Only local sensing. No global coordinates. Robots have pre-assigned id's and positions in formation.
- Social patterns for scalable multi robot formations. Balch Hybinette
Simulation study. Fixed formation. Not fixed positions within formation. Motor schema vector summation. Performance measures of different formations by crossing obstacle filled arena.
- Cellular Robotic Systems - Self Organizing Robots and Kinetic Pattern Generation Wang Beni
Grid space. Rules to generate patterns. Generic algorithm to generate given pattern. Guaranteed to terminate.
- Superlinear physical performances in a SWARM-BOT
Discusses optimal structures (size rather than shape) for various tasks and the relative performance increase of adding subsequent sbots. Could be used to justify i) Star shape chain size ii) Group size selection mechanism.
- SWARM-BOT - Pattern formation in a swarm of self-assembling mobile robots. Sahin
Swarmbot project. Simulation only. Hexagonal grid world. Probabilistic assembly. Statistical analysis of structures formed. e.g. length of chains, frequency.
- Steps towards self-reconfigurable robot systems by modelling cellular adhesion. Ottery, Hallam
Simulation only. Simple heirarchical patterns based on cell membrane type interactions (A-CAM). Paper we reviewed was partially based on this.
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- Gradual spatial pattern formation of homogeneous robot group. Fukuda. (Science Direct)