An application of lyapunov stability analysis to improve the performance of NARMAX models

Previously we presented a novel approach to program a robot controller based on system identification and robot training techniques. The proposed method works in two stages: first, the programmer demonstrates the desired behaviour to the robot by driving it manually in the target environment. During this run, the sensory perception and the desired velocity commands of the robot are logged. Having thus obtained training data we model the relationship between sensory readings and the motor commands of the robot using ARMAX/NARMAX models and system identification techniques. These produce linear or non-linear polynomials which can be formally analysed, as well as used in place of “traditional robot” control code. In this paper we focus our attention on how the mathematical analysis of NARMAX models can be used to understand the robot’s control actions, to formulate hypotheses and to improve the robot’s behaviour. One main objective behind this approach is to avoid trial-and-error refinement of robot code. Instead, we seek to obtain a reliable design process, where program design decisions are based on the mathematical analysis of the model describing how the robot interacts with its environment to achieve the desired behaviour. We demonstrate this procedure through the analysis of a particular task in mobile robotics: door traversal

Requirements for implementing real-time control functional modules on a hierarchical parallel pipelined system

Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored

Towards a universal end effector : the design and development of production technology's intelligent robot hand : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Engineering and Automation at Massey University

Research into robot hands for industrial use began in the early 1980s and there are now many examples of robot hands in existence. The reason for research into robot hands is that standard robot end effectors have to be designed for each application and are therefore costly. A universal end effector is needed that will be able to perform any parts handling operation or use other tools for other industrial operations. Existing robot hand research would therefore benefit from new concepts, designs and control systems. The Department of Production Technology is developing an intelligent robot hand of a novel configuration, with the ultimate aim of producing a universal end effector. The concept of PTIRH (Production Technology's Intelligent Robot Hand) is that it is a multi-fingered manipulator with a configuration of two thumbs and two fingers. Research by the author for this thesis concentrated on five major areas. First, the background research into the state of the art in robot hand research. Second, the initiation, development and analysis of the novel configuration concept of PTIRH. Third, specification, testing and analysis of air muscle actuation, including design, development and testing of a servo pneumatic control valve for the air muscles. Fourth, choice of sensors for the robot hand, including testing and analysis of two custom made air pressure sensors. Fifth, definition, design, construction, development, testing and analysis of the mechanical structure for an early prototype of PTIRH. Development of an intelligent controller for PTIRH was outside the scope of the author's research. The results of the analysis on the air muscles showed that they could be a suitable direct drive actuator for an intelligent robotic hand. The force, pressure and position sensor results indicate that the sensors could form the basis of the feedback loop for an intelligent controller. The configuration of PTIRH enables it to grasp objects with little reliance on friction. This was demonstrated with an early prototype of the robot hand, which had one finger with actuation and three other static digits, by successfully manually arranging the digits into stable grasps of various objects

Model identification and model analysis in robot training

Robot training is a fast and efficient method of obtaining robot control code. Many current machine learning paradigms used for this purpose, however, result in opaque models that are difficult, if not impossible to analyse, which is an impediment in safety-critical applications or application scenarios where humans and robots occupy the same workspace. In experiments with a Magellan Pro mobile robot we demonstrate that it is possible to obtain transparent models of sensor-motor couplings that are amenable to subsequent analysis, and how such analysis can be used to refine and tune the models post hoc

Robot programming by demonstration through system identification

Increasingly, personalised robots — robots especially designed and programmed for an individual’s needs and preferences — are being used to support humans in their daily lives, most notably in the area of service robotics. Arguably, the closer the robot is programmed to the individual’s needs, the more useful it is, and we believe that giving people the opportunity to program their own robots, rather than programming robots for them, will push robotics research one step further in the personalised robotics field. However, traditional robot programming techniques require specialised technical skills from different disciplines and it is not reasonable to expect end-users to have these skills. In this paper, we therefore present a new method of obtaining robot control code — programming by demonstration through system identification which algorithmically and automatically transfers human behaviours into robot control code, using transparent, analysable mathematical functions. Besides providing a simple means of generating perception-action mappings, they have the additional advantage that can also be used to form hypotheses and theoretical analysis of robot behaviour. We demonstrate the viability of this approach by teaching a Scitos G5 mobile robot to achieve wall following and corridor passing behaviours

Mobile robot based electrostatic spray system for controlling pests on cotton plants in Iraq

A mobile robot based electrostatic spray system was developed to combat pest infestation on cotton plants in Iraq. The system consists of a charged spray nozzle, a CCD camera, a mobile robot (vehicle and arm) and Arduino microcontroller. Arduino microcontroller is used to control the spray nozzle and the robot. Matlab is used to process the image from the CCD camera and to generate the appropriate control signals to the robot and the spray nozzle. COMSOL multi-physics FEM software was used to design the induction electrodes to achieve maximum charge transfer onto the fan spray liquid film resulting in achieving the desired charge/mass ratio of the spray. The charged spray nozzle was operated on short duration pulsed spray mode. Image analysis was employed to investigate the spray deposition on improvised insect targets on an artificial plant.The ministry of higher education and scientific research of Iraqi governmen

On Grasping a Tumbling Debris Object with a Free-Flying Robot

The grasping and stabilization of a tumbling, non-cooperative target satellite by means of a free-flying robot is a challenging control problem, which has been addressed in increasing degree of complexity since 20 years. A novel method for computing robot trajectories for grasping a tumbling target is presented. The problem is solved as a motion planning problem with nonlinear optimization. The resulting solution includes a first maneuver of the Servicer satellite which carries the robot arm, taking account of typical satellite control inputs. An analysis of the characteristics of the motion of a grasping point on a tumbling body is used to motivate this grasping method, which is argued to be useful for grasping targets of larger size