Benefits of an Active Spine Supported Bounding Locomotion With a Small Compliant Quadruped Robot

We studied the effect of the control of an active spine versus a fixed spine, on a quadruped robot run- ning in bound gait. Active spine supported actuation led to faster locomotion, with less foot sliding on the ground, and a higher stability to go straight forward. However, we did no observe an improvement of cost of transport of the spine-actuated, faster robot system compared to the rigid spine

Rich Locomotion Skills with the Oncilla Robot

We are motivated to better understand how adaptive locomotion (rough terrain locomotion, turning, gait transition, etc) can be realized using a quadrupedal platform with constrained resources. These constraints include computational power limitation, no accurate force/torque sensing, and partial sensing of robot’s kinematic states. These constraints arise from the fact that we are designing and experimenting with autonomous light-weight and (comparatively) cheap quadruped robots. The practical benefit of such robots is fast experimentation: experiments can be safely done with presence of one or two humans, and repairs are cheap and quick

Towards Modular Control for Moderately Fast Locomotion over Unperceived Rough Terrain

We are motivated to build simple controllers for quadruped robots to locomote over unperceived moderately difficult rough terrain at moderately fast speeds. The presented approach here does not need force sensing at feet, and does not need information about the mass properties of the robot like inertia tensors, so it is apt for relatively cheap and lightweight robots. We explore our approach with two dif- ferent simulated robots, one being the simulation of the Oncilla robot which will soon be used for validation

Spinal joint compliance and actuation in a simulated bounding quadruped robot

Spine movements play an important role in quadrupedal locomotion, yet their potential benefits in locomotion of quadruped robots have not been systematically explored. In this work, we investigate the role of spinal joint actuation and compliance on the bounding performance of a simulated compliant quadruped robot. We designed and conducted extensive simulation experiments, to compare the benefits of different spine designs, and in particular, we compared the bounding performance when (i) using actuated versus passive spinal joint, (ii) changing the stiffness of the spinal joint and (iii) altering joint actuation profiles. We used a detailed rigid body dynamics modeling to capture the main dynamical features of the robot. We applied a set of analytic tools to evaluate the bounding gait characteristics including periodicity, stability, and cost of transport. A stochastic optimization method called particle swarm optimization was implemented to perform a global search over the parameter space, and extract a pool of diverse gait solutions. Our results show improvements in bounding speed for decreasing spine stiffness, both in the passive and the actuated case. The results also suggests that for the passive spine configuration at low stiffness values, periodic solutions are hard to realize. Overall, passive spine solutions were more energy efficient and self-stable than actuated ones, but they basically exist in limited regions of parameter space. Applying more complex joint control profiles reduced the dependency of the robot's speed to its chosen spine stiffness. In average, active spine control decreased energy efficiency and self-stability behavior, in comparison to a passive compliant spine setup