David Wilkie's Bio-Inspired Robot Project
This class is emphasizing the construction of comprehensive models for bio-inspired robots. "Bio-inspired" means inspired by evolution's solutions to various problems (my definition). For example, ant colonies use a stigmergic search strategy to find food: they walk in random paths; when one finds a source of food, it starts leaving a chemical path as it returns to the nest; this path compels other ants to follow, similar in result to the local beam search (which, in the words of Stuart Russel or Peter Norvig, says "Come over here, the grass is greener!"). This "meta-heuristic," inspired by nature, has been successfully applied to optimization problems. In this class, our interest is robots inspired by nature's various methods of motion.
For most students in the class, the initial model is, somewhat paradoxically, the physical model. That is, it is some lego or similar creation capable of undertaking some bio-inspired gait (wheels need not apply). This is an ideal initial model due to the simplicity and versatility of legos. Prototyping with legos can occur much quicker than in a CAD system (at for users with no experience with CAD).
Software, hardware, power, sensors and their interactions CAD/3D/Assembly Modeling Geometry, topology, constraints, joints and features Functional Modeling Intended use (or function) for the device (note, device may have other unintended functions or uses) Behavioral Modeling System inputs/outputs, motion characteristic, etc that achieve the function Physics-based modeling Statics, kinematics, dynamics and laws of physics Information Modeling Data, relationships, semantics (meaning)