Development of manufacturing technique for composite structures for robotic applications

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 23-25).An experimental study was performed with the aim of developing a technique for manufacturing composite parts for use in dynamic robotic applications in lieu of heavy and expensive metal parts used in conventional robotic systems. There is already a wide usage of sandwich board materials in load bearing applications, but these do not provide equal strength in all directions, particularly compressive strength. Additionally, these materials are only available in two-dimensional shapes. The process developed over the course of this project seeks to make a fully covered composite of any desired geometries. The specific robotics project addressed was the hyper dynamic quadruped robotic platform, which ultimately seeks to design and construct a robot capable of a high speed gallop. This thesis began exploring methods of fabricating parts for one of the legs of the platform, specifically a radius part. Manufactured components needed to be both light in weight to facilitate ease of movement for the robot and strong enough to withstand the forces from the shifting weight during running. Proposed design parameters called for a foam core with a hard plastic shell to meet these needs. This technique can lead to a cheaper manufacturing method with a potential impact on the future robotics industry. After an investigation into the properties of different liquid polyurethane foams and plastics, the manufacturing techniques explored began with machining molds for both the inner core and outer shell of composite parts into wax blocks. The project aims were to develop a prototyping process, but this can lead to mass-production. Two versions of a manufacturing process with these blocks were developed, one which uses an open mold and one which uses a closed mold. Either method is viable for fabrication, with a preference for the open mold in parts with simple geometry and small thickness, and for the closed mold in larger parts or ones with complicated or interrupted outer perimeters.by Theresa Dixon.S.B

FUZZY BASED SELF-TRANSFORMING ROBOT

ABSTRACT Self-transforming robot is a robot which transforms its shape according to the hindrance occurring in the path where the robots are being moved. Such robots have been recognized as very attractive design in exhibiting the reliable transformation according to the situations. Military and defense application needs a robot should possess arbitrary movements like human. In some scenarios transformations are made by biological inspired control strategies using Central Pattern Generators (CPG). CPG is used in the locomotion control of snake robots, quadruped robots, to humanoid robots. This paper presents a Fuzzy system for the Self-transforming robot which possess alteration in its original shape to exhibit a human-like behavior while passing over the particular location. Quadrupedal locomotion on rough terrain and unpredictable environments is still a challenge, where the proposed system will provide the good adaptability in rough terrain. It allows the modulation of locomotion by simple control signal. The necessary conditions for the stable dynamic walking on irregular terrain in common are proposed. Extensive simulations are carried out to validate the performance of the proposed Fuzzy system using LABVIEW. Arbitrary parameters such as distance, angle and orientation of the obstacles are provided as input to the fuzzy system which gives the required speed modulation on the motoric module

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

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

Automatic Gait Generation in Modular Robots: to Oscillate or to Rotate? that is the question

Modular robots offer the possibility to design robots with a high diversity of shapes and functionalities. This nice feature also brings an important challenge: namely how to design efficient locomotion gaits for arbitrary robot structures with many degrees of freedom. In this paper, we present a framework that allows one to explore and identify highly different gaits for a given arbitraryshaped modular robot. For this, we use simulated robots made of several Roombots modules that have three rotational joints each. These modules have as interesting feature that they can produce both oscillatory movements (i.e. periodic movements around a rest position) and rotational movements (i.e. with continuously increasing angle), leading to very rich locomotion patterns. Here we ask ourselves which types of movements — purely oscillatory, purely rotational, or a combination of both— lead to the fastest gaits. To address this question we designed a control architecture based on a distributed system of coupled phase oscillators that can produce synchronized rotations and oscillations in many degrees of freedom. We also designed a specific optimization algorithm that can automatically design hybrid controllers, i.e. controllers that use oscillations in some joints and rotations in others, for fast gaits. The proposed framework is verified through multiple simulations for several robot morphologies. The results show that (i) the question whether it is better to oscillate or to rotate depends on the morphology of the robot, and that in general it is best to do both, (ii) the optimization framework can successfully generate hybrid controllers that outperform purely oscillatory and purely rotational ones, and (iii) the resulting gaits are fast, innovative, and would have been hard to design by han

Prescription of rhythmic patterns for legged locomotion

As the engine behind many life phenomena, motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree-of-freedom (DOF) with adjustable oscillatory frequencies and duty cycles. An OBBs network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration

Combining series elastic actuation and magneto-rheological damping for the control of agile locomotion

All-terrain robot locomotion is an active topic of research. Search and rescue maneuvers and exploratory missions could benefit from robots with the abilities of real animals. However, technological barriers exist to ultimately achieving the actuation system, which is able to meet the exigent requirements of these robots. This paper describes the locomotioncontrol of a leg prototype, designed and developed to make a quadruped walk dynamically while exhibiting compliant interaction with the environment. The actuation system of the leg is based on the hybrid use of series elasticity and magneto-rheological dampers, which provide variable compliance for natural-looking motion and improved interaction with the ground. The locomotioncontrol architecture has been proposed to exploit natural leg dynamics in order to improve energy efficiency. Results show that the controller achieves a significant reduction in energy consumption during the leg swing phase thanks to the exploitation of inherent leg dynamics. Added to this, experiments with the real leg prototype show that the combined use of series elasticity and magneto-rheologicaldamping at the knee provide a 20 % reduction in the energy wasted in braking the knee during its extension in the leg stance phase