Gait control for obstacle negotiation in canines


SOCIETY FOR INTEGRATIVE AND COMPARATIVE BIOLOGY
2021 VIRTUAL ANNUAL MEETING (VAM)
January 3 – Febuary 28, 2021

Meeting Abstract


14-2  Sat Jan 2  Gait control for obstacle negotiation in canines Joyce, M*; Wilshin, S; Qian, F; Spence, A; Temple University; Royal Veterinary College; University of Southern California; Temple University michelle.joyce@temple.edu

Understanding the biomechanics of how animals overcome complex environments has significant implications in biology and engineering. These include obstacle negotiation, neural and mechanical control, and applications in robotics as biological systems remain superior in this domain. Here we examine how flexibly controlled quadrupedal obstacle negotiation is constrained by the structure of typical animal gaits and the environment. Past research has found that as a quadrupedal robot moves over a regular array of domed obstacles, gait type and obstacle contact result in stable locomotion with a systematic change in direction. As dogs have additional flexibility and must consider tradeoffs between desired gait, navigation, and energy expenditure, we hypothesized that in a similar array, dogs would change gait parameters including duty factor, limb phase, stride length, as well as direction of locomotion. To begin investigating the effect of space between obstacles, we quantified the natural step length of eleven dogs, and used this to normalize spacing for body size. Spacing was also increased and decreased by 20% from that value. For one adaptation, we hypothesized that with longer spacing, dogs would spend less time with their paws on the ground, thus having a lower duty factor. Preliminary results do indicate a negative relationship between spacing size and duty factor. Using a generalized linear mixed effects model, the effect size was -1.86, with standard error 0.14, p<0.01, for n=11 dogs. Continuing analysis of additional parameters will further investigate a dog’s ability to cope with obstacle fields. Adapting these strategies in robotic systems will allow for greater flexibility in cluttered environments by employing more stable and economical locomotion.

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