Role of Compliance on the Locomotion of a Reconfigurable Modular Snake Robot

This paper presents the results of a study on the effect of in-series compliance on the locomotion of a simulated 8-DoF Lola-OP Modular Snake Robot with added compliant elements. We explore whether there is an optimal stiffness for gait, terrain type, or several gaits and several terrains (i.e. a good “general-purpose” stiffness). Compliance was simulated using ball joints with eight different levels of stiffness. Two snake locomotion gaits (rolling and sidewinding) were tested over flat ground and three different types of rough terrains. We performed grid search and Particle Swarm Optimization to identify the locomotion parameters leading to fast locomotion and analyzed the best candidates in terms of locomotion speed and energy efficiency (cost of transport). Contrary to our expectations, we did not observe a clear trend that would favor the use of compliant elements over rigid structures. For sidewinding, compliant and stiff elements lead to comparable performances. For rolling gait, the general rule seems to be “the stiffer, the better”.

Gait Optimization for Roombots Modular Robots - Matching Simulation and Reality

Stéphane Bonardi, Auke Ijspeert, Soha Pouya, Jesse van den Kieboom, Massimo Vespignani

The design of efficient locomotion gaits for robots with many degrees of freedom is challenging and time consuming even if optimization techniques are applied. Control parameters can be found through optimization in two ways: (i) through online optimization where the performance of a robot is measured while trying different control parameters on the actual hardware and (ii) through offline optimization by simulating the robot's behavior with the help of models of the robot and its environment. In this paper, we present a hybrid optimization method that combines the best properties of online and offline optimization to efficiently find locomotion gaits for arbitrary structures. In comparison to pure online optimization, both the number of experiments using robotic hardware as well as the total time required for finding efficient locomotion gaits get highly reduced by running the major part of the optimization process in simulation using a cluster of processors. The presented example shows that even for robots with a low number of degrees of freedom the time required for optimization can be reduced by a factor of 2.5 to 30, at least, depending on how extensive the search for optimized control parameters should be. Time for hardware experiments becomes minimal. More importantly, gaits that can possibly damage the robotic hardware can be filtered before being tried in hardware. Yet in contrast to pure offline optimization, we reach well matched behavior that allows a direct transfer of locomotion gaits from simulation to hardware. This is because through a meta-optimization we adapt not only the locomotion parameters but also the parameters for simulation models of the robot and environment allowing for a good matching of the robot behavior in simulation and hardware. We validate the proposed hybrid optimization method on a structure composed of two Roombots modules with a total number of six degrees of freedom. Roombots are self-reconfigurable modular robots that can form arbitrary structures with many degrees of freedom through an integrated active connection mechanism.

Ieee2013

Gait Optimization for Roombots Modular Robots - Matching Simulation and Reality

Stéphane Bonardi, Auke Ijspeert, Rico Möckel, Soha Pouya, Alexander Spröwitz, Massimo Vespignani

The design of efficient locomotion gaits for robots with many degrees of freedom is challenging and time con- suming even if optimization techniques are applied. Control parameters can be found through optimization in two ways: (i) through online optimization where the performance of a robot is measured while trying different control parameters on the actual hardware and (ii) through offline optimization by simulating the robot’s behavior with the help of models of the robot and its environment. In this paper, we present a hybrid optimization method that combines the best properties of online and offline optimization to efficiently find locomotion gaits for arbitrary structures. In comparison to pure online optimization both the number of experiments using robotic hardware as well as the total time required for finding efficient locomotion gaits get highly reduced by running the major part of the optimization process in simulation using a cluster of processors. The presented example shows that even for robots with a low number of degrees of freedom the time required for optimization can be reduced by at least a factor of 2.5 to 30 depending on how extensive the search for optimized control parameters should be. Time for hardware experiments becomes minimal. More importantly gaits that can possibly damage the robotic hardware can be filtered before being tried. Yet in contrast to pure offline optimization we reach well matched behavior that allows a direct transfer of locomotion gaits from simulation to hardware. This is because through a meta-optimization we adapt not only the locomotion parameters but also the parameters for simulation models of the robot and environment allowing for a good matching of the behavior of simulated and hardware robot structures. We verify the proposed hybrid optimization method on a structure composed of two Roombots modules. Roombots are self-reconfigurable modular robots that can form arbitrary structures with many degrees of freedom through an integrated active connection mechanism.

2013

Compliant snake robot locomotion on horizontal pipes

Auke Ijspeert, Kamilo Andres Melo Becerra, Mehmet Hasan Mutlu, Massimo Vespignani

In this paper we introduce a body-compliant Modular Snake Robot executing rolling gaits on different cylindrical geometries. In the state of the art it is considered that an active shape adaptation to the terrain while a gait is executed produces better performances than a simple pre-programmed stiff motion without feedback. Several attempts to reproduce such behaviors in snake robots range from compliant shape controllers (acting in joint space) to torque control strategies of elastic actuated joints. In our proposal, we incorporate compliant elements in a modular snake robot structure to passively adapt the robot’s shape to the environment. The gait control remains simple by acting directly in the robot’s joint space with known gait generation schemes. To validate our results we performed experiments with compliant modular snake robots rolling on pipes with different geometry characteristics such as different diameters, smooth surfaces, surfaces with presence of obstacles (terrain bumps), and considerable changes in diameter in a single robot run. We evaluated the performance across different robot’s body-compliance values, measuring the speed of locomotion as well as the power consumption. Our results show that providing a good selection of body compliant elements is a way to maintain high locomotion performance (at least while rolling on pipes) without including additional complex control artifacts to the simple open-loop cyclic gait controller.

2015

Gait Optimization for Roombots Modular Robots - Matching Simulation and Reality

Stéphane Bonardi, Auke Ijspeert, Soha Pouya, Jesse van den Kieboom, Massimo Vespignani

Ieee2013

Gait Optimization for Roombots Modular Robots - Matching Simulation and Reality

Stéphane Bonardi, Auke Ijspeert, Rico Möckel, Soha Pouya, Alexander Spröwitz, Massimo Vespignani

2013