Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation

An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can perform various walking behaviors. However, such a single chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based on a simulated annealing algorithm. In a normal situation, the CPGs synchronize and their dynamics are identical. With leg malfunction or disability, the CPGs lose synchronization leading to independent dynamics. In this case, the learning mechanism is applied to automatically adjust the remaining legs' oscillation frequencies so that the robot adapts its locomotion to deal with the malfunction. As a consequence, the trajectory produced by the multiple chaotic CPGs resembles the original trajectory far better than the one produced by only a single CPG. The performance of the system is evaluated first in a physical simulation of a quadruped as well as a hexapod robot and finally in a real six-legged walking machine called AMOSII. The experimental results presented here reveal that using multiple CPGs with learning is an effective approach for adaptive locomotion generation where, for instance, different body parts have to perform independent movements for malfunction compensation.Comment: 48 pages, 16 figures, Information Sciences 201

Optimal Design Methods for Increasing Power Performance of Multiactuator Robotic Limbs

abstract: In order for assistive mobile robots to operate in the same environment as humans, they must be able to navigate the same obstacles as humans do. Many elements are required to do this: a powerful controller which can understand the obstacle, and power-dense actuators which will be able to achieve the necessary limb accelerations and output energies. Rapid growth in information technology has made complex controllers, and the devices which run them considerably light and cheap. The energy density of batteries, motors, and engines has not grown nearly as fast. This is problematic because biological systems are more agile, and more efficient than robotic systems. This dissertation introduces design methods which may be used optimize a multiactuator robotic limb's natural dynamics in an effort to reduce energy waste. These energy savings decrease the robot's cost of transport, and the weight of the required fuel storage system. To achieve this, an optimal design method, which allows the specialization of robot geometry, is introduced. In addition to optimal geometry design, a gearing optimization is presented which selects a gear ratio which minimizes the electrical power at the motor while considering the constraints of the motor. Furthermore, an efficient algorithm for the optimization of parallel stiffness elements in the robot is introduced. In addition to the optimal design tools introduced, the KiTy SP robotic limb structure is also presented. Which is a novel hybrid parallel-serial actuation method. This novel leg structure has many desirable attributes such as: three dimensional end-effector positioning, low mobile mass, compact form-factor, and a large workspace. We also show that the KiTy SP structure outperforms the classical, biologically-inspired serial limb structure.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201

Soft Actuators and Robots that Are Resistant to Mechanical Damage

This paper characterizes the ability of soft pneumatic actuators and robots to resist mechanical insults that would irreversibly damage or destroy hard robotic systems—systems fabricated in metals and structural polymers, and actuated mechanically—of comparable sizes. The pneumatic networks that actuate these soft machines are formed by bonding two layers of elastomeric or polymeric materials that have different moduli on application of strain by pneumatic inflation; this difference in strain between an extensible top layer and an inextensible, strain-limiting, bottom layer causes the pneumatic network to expand anisotropically. While all the soft machines described here are, to some extent, more resistant to damage by compressive forces, blunt impacts, and severe bending than most corresponding hard systems, the composition of the strain-limiting layers confers on them very different tensile and compressive strengths.Chemistry and Chemical BiologyOther Research Uni

A Hybrid Combining Hard and Soft Robots

This manuscript describes a hybrid robotic system combining hard and soft sub-systems. This hybrid comprises a wheeled robot (an iRobot Create©; hard) and a four-legged quadruped (soft). It is capable (using a simple, wireless control system) of rapid locomotion over flat terrain (using the wheeled hard robot), and of gripping and retrieval of an object (using the soft robot). The utility of this system is demonstrated by performing a mission requiring the capabilities of both components: retrieving an object (iPod Nano®) from the center of a room. This class of robot— hybrids comprising hard and soft systems functioning synergistically—is capable of performing tasks that neither can do alone. In contrast to specialised hard robotic arms with grippers (capable of performing some of the functions we describe here), which are complex, relatively expensive, and require sophisticated controls, this hybrid system is easy to construct, simple to control, and low in cost. The soft robotic system in the hybrid is lightweight, disposable if contaminated or damaged, and capable of multiple functions.Chemistry and Chemical Biolog