Psychologically Inspired Sensory-Motor Development in Early Robot Learning

Lee, M., Meng, Q. (2005). Psychologically Inspired Sensory-Motor Development in Early Robot Learning. International Journal of Advanced Robotic Systems, 325-334.

Psychologically Inspired Sensory-Motor Development in Early Robot Learning

M.H. Lee and Q. Meng, 'Psychologically Inspired Sensory-Motor Development in Early Robot Learning', in proceedings of Towards Autonomous Robotic Systems 2005 (TAROS-05), Nehmzow, U., Melhuish, C. and Witkowski, M. (Eds.), Imperial College London, 157-163, September 2005. See published version: http://hdl.handle.net/2160/485

Dynamical Systems in the Sensorimotor Loop: On the Interrelation Between Internal and External Mechanisms of Evolved Robot Behavior

Huelse, M., Wischmann, S., Manoonpong, P., Twickel, A.v., Pasemann, F.: Dynamical Systems in the Sensorimotor Loop: On the Interrelation Between Internal and External Mechanisms of Evolved Robot Behavior. In: M. Lungarella, F. Iida, J. Bongard, R. Pfeifer (Eds.) 50 Years of Artificial Intelligence, LNCS 4850, Springer, 186 - 195, 2007.

Cellular automata and non-static image processing for embodied robot systems on a massively parallel processor array

Huelse, M, Barr, D R W, Dudek, P: Cellular Automata and non-static image processing for embodied robot systems on a massively parallel processor array. In: Adamatzky, A et al. (eds) AUTOMATA 2008, Theory and Applications of Cellular Automata. Luniver Press, 2008, pp. 504-510. Sponsorship: EPSRC

Diseño y fabricación de una tarjeta PCB (Shield) para el control de un robot autobalanceado basado en Arduino

Un robot autobalanceado es un dispositivo que, aun teniendo su centro de masas por encima del eje de giro, consigue mantener el equilibrio. Se basa o aproxima al problema del péndulo invertido. Este proyecto comprende el desarrollo e implementación de un robot autobalanceado basado en la plataforma Arduino. Se utilizará una placa Arduino y se diseñará y fabricará con un shield o tarjeta (PCB), donde se incluirán los elementos hardware que se consideren necesarios. Abarca el estudio y montaje del chasis y los sistemas de sensado, control digital, alimentación y motores

Navite: A Neural Network System For Sensory-Based Robot Navigation

A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.

Unsupervised Neural Network for the Control of a Mobile Robot

This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.

COGNITIVE ASSESSMENT USING THE KINARM EXOSKELETON ROBOT IN PATIENTS WITH TRANSIENT ISCHEMIC ATTACK

Background: Transient ischemic attack (TIA) is a condition causing focal neurological deficits lasting less than 24hrs. TIA patients present similarly to other conditions with rapid onset of neurological symptoms such as migraine. The accurate diagnosis of TIA is critical because it serves as a warning for subsequent stroke. Furthermore, cognitive deficit associated with TIA may predict the development of dementia. Therefore, characterizing the cognitive symptoms of TIA patients and discriminating these patients from those with similar symptoms is important for proper diagnosis and treatment. Currently the diagnosis of TIA is made on clinical and radiographic evidence. Robotic assessment, with instruments such as the KINARM, may improve the identification of cognitive impairment in TIA patients. Methods: In this prospective cohort study, two KINARM tests, trail making task (TMT) and spatial span task (SST), were used to detect cognitive deficits. Two study groups were made. The TIA group was tested at 5 time points over the span of a year. The migraine active control group had one initial visit and another a year later. Both of these groups were compared to a normative database of approximately 400 healthy volunteers. From this database age and sex matched normative data was used to calculate Z-scores for the TMT. The Montreal Cognitive Assessment (MoCA) was also administered to both groups. Results: 31 participants were recruited, 20 TIA group and 11 active controls (mean ± SD age= 66 ± 11.3 and 62 ± 14.5). There was no significant difference in TIA and active control group MoCA scores. The TMT was able to detect cognitive impairment in TIA and migraine group. Also, both KINARM tasks could detect significant differences in performance between TIA and migraine patients while the MoCA could not. Changes in TIA and migraine performance on the MoCA, TMT, and SST were observed. Conclusions: The robotic KINARM exoskeleton can be used to assess cognitive deficits in TIA patients.

Estimating the Heading of a Husky Mobile Robot with a LiDAR Compass based on Direction Maps

Without an absolute position sensor (e.g., GPS), an accurate heading estimate is necessary for proper localization of an autonomous unmanned vehicle or robot. This paper introduces direction maps (DMs), which represent the directions of only dominant surfaces of the vehicle’s environment and can be created with negligible effort. Given an environment with reoccurring surface directions (e.g., walls, buildings, parked cars), lines extracted from laser scans can be matched with a DM to provide an extremely lightweight heading estimate that is shown, through experimentation, to drastically reduce the growth of heading errors. The algorithm was tested using a Husky A200 mobile robot in a warehouse environment over traverses hundreds of metres in length. When a simple a priori DM was provided, the resulting heading estimation showed virtually no error growth.

Parallel Robot

Parallel robot (PR) is a mechanical system that utilized multiple computer-controlled limbs to support one common platform or end effector. Comparing to a serial robot, a PR generally has higher precision and dynamic performance and, therefore, can be applied to many applications. The PR research has attracted a lot of attention in the last three decades, but there are still many challenging issues to be solved before achieving PRs’ full potential. This chapter introduces the state-of-the-art PRs in the aspects of synthesis, design, analysis, and control. The future directions will also be discussed at the end.