The science behind animal-inspired robotics

The science behind animal-inspired robotics

The 21st Century has seen an explosion of bio-inspired technology and devices. Perhaps no where has this approach been more transformative than in the field of mobile robotics. Geckos, snakes, and even cockroaches have motivated new sticky, stable, steerable robots. Yet inspiration means more than curiosity. As scientists we must unravel the scientific principles and mechanisms underlying animal performance. By studying the physics of these living systems we can inform a systematic approach to animal-inspired robotics. By doing so, we discover new properties and dynamics of complex systems -- the robots themselves even...

Date

November 10, 2014 - 1:00pm

Location

CULC Room 144

The 21st Century has seen an explosion of bio-inspired technology and devices. Perhaps no where has this approach been more transformative than in the field of mobile robotics. Geckos, snakes, and even cockroaches have motivated new sticky, stable, steerable robots. Yet inspiration means more than curiosity. As scientists we must unravel the scientific principles and mechanisms underlying animal performance. By studying the physics of these living systems we can inform a systematic approach to animal-inspired robotics. By doing so, we discover new properties and dynamics of complex systems -- the robots themselves even become experimental platforms to test hypotheses. We can learn the pitfalls of ignoring the evolutionary context that shaped animal locomotion and the power of non-dimensional ratios that scale across biology. In this talk, we will first explore how human technology is taking on more characteristics for which the natural world is a better teacher. We will then use several examples over the past decade of robotics research where animals have served as the inspiration, but where identification of the underlying physics has led to innovation. Finally we will discuss how new bio-physical insights emerged from studying the resulting robots as physical models for the biological systems.