Templates and anchors for antenna-based wall following in cockroaches and robots

The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model. © 2008 IEEE.

Towards soft self-reconfigurable robots

Modular self-reconfigurable robots have previously demonstrated that automatic control of their own body shapes enriches their behavioural functions. However, having predefined rigid modules technically limits real-world systems from being hyper-redundant and compliant. Encouraged by recent progress using elastically deformable material for robots, we propose the concept of soft self-reconfigurable robots which may become hyper-flexible during interaction with the environment. As the first attempt towards this goal, the paper proposes a novel approach using viscoelastic material Hot-Melt Adhesives (HMAs): for physical connection and disconnection control between bodies that are not necessarily predefined rigid modules. We present a model that characterizes the temperature dependency of the strength of HMA bonds, which is then validated and used in a feedback controller for automatic connection and disconnection. Using a minimalistic robot platform that is equipped with two devices handling HMAs, the performance of this method is evaluated in a pick-and-place experiment with aluminium and wooden parts. © 2012 IEEE.

Twitching in sensorimotor development from sleeping rats to robots.

It is still not known how the 'rudimentary' movements of fetuses and infants are transformed into the coordinated, flexible and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: when twitches are mimicked in robot models of the musculoskeletal system, the basic neural circuitry undergoes self-organization. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain.

AI in locomotion: Challenges and perspectives of underactuated robots

This article discusses the issues of adaptive autonomous navigation as a challenge of artificial intelligence. We argue that, in order to enhance the dexterity and adaptivity in robot navigation, we need to take into account the decentralized mechanisms which exploit physical system-environment interactions. In this paper, by introducing a few underactuated locomotion systems, we explain (1) how mechanical body structures are related to motor control in locomotion behavior, (2) how a simple computational control process can generate complex locomotion behavior, and (3) how a motor control architecture can exploit the body dynamics through a learning process. Based on the case studies, we discuss the challenges and perspectives toward a new framework of adaptive robot control. © Springer-Verlag Berlin Heidelberg 2007.

coconceptmap: a system for collaborative concept mapping

Concept mapping is a technique for visualizing the relationships between different concepts, and collaborative concept mapping is used to model knowledge and transfer expert knowledge. Because of lacking some features,existing systems can’t support collaborative concept mapping effectively. In this paper, we analysis the collaborative concept mapping process according to the theory of distributed cognition, and argue the functions effective systems ought to include. A collaborative concept mapping system should have the following features: visualization of concept map, flexible collaboration style,supporting natural interaction, knowledge management and history management. Furthermore, we describe every feature in details. Finally,a prototype system has been built to fully explore the above technologies.

incremental learning of triadic plsa for collaborative filtering

Beijing University of Technology (BJUT); Beijing Municipal Lab of Brain Informatics; Chinese Society of Radiology; National Natural Science Foundation of China (NSFC); State Administration of Foreign Experts Affairs

自主移动机器人足球比赛视觉定位方法综述

综述了RoboCup足球赛中全自主移动机器人基于视觉的定位技术,包括机器人自定位和多机器人协作物体定位.介绍了定位技术的发展情况与分类.从机器人环境构建形式的不同以及先验位姿和概率方法的应用与否等方面,系统地分析和比较了各种自定位方法.对于多机器人协作物体定位,阐述了静态方法和动态跟踪方法.总结了定位过程中需要重点研究的传感器模型构建、图像处理、特征匹配以及协作过程涉及的相关问题.最后就视觉定位存在的问题和技术发展趋势进行了讨论.

Theoretical and experimental research on time-optimal trajectory planning and control of industrial robots

提出了一种用于工业机器人时间最优轨迹规划及轨迹控制的新方法，它可以确保在关节位移、速度、加速度以及二阶加速度边界值的约束下，机器人手部沿笛卡尔空间中规定路径运动的时间阳短。在这种方法中，所规划的关节轨迹都采用二次多项式加余弦函数的形式，不仅可以保证各关节运动的位移、速度 、加速度连续而且还可以保证各关节运动的二阶加速度连续。采用这种方法，既可以提高机器人的工作效率又可以延长机器人的工作寿命以PUMA560机器人为对象进行了计算机仿真和机器人实验，结果表明这种方法是正确的有效的。它为工业机器人在非线性运动学约束条件下的时间最优轨迹规划及控制问题提供了一种较好的解决方案。

Stabilization of Dynamic Systems for Multiple Omni-Directional Mobile Robots

本文考虑了由2个全方位移动机器人组成的混合动力学系统的协调拟镇定问题.利用机器人位置之间的向量与机器人目标之间向量的内积,设计了多步拟镇定律,该控制律能够在避碰后按指数速率运动到目标点,且在整个过程中两机器人之间的距离不小于避碰的安全距离.最后对2个全方位移动机器人进行了仿真,验证了所给方法的有效性。

The effect of the product cost factor on error handling in industrial robots

N.W. Hardy and M.H. Lee. The effect of the product cost factor on error handling in industrial robots. In Maria Gini, editor, Detecting and Resolving Errors in Manufacturing Systems. Papers from the 1994 AAAI Spring Symposium Series, pages 59-64, Menlo Park, CA, March 1994. The AAAI Press. Technical Report SS-94-04, ISBN 0-929280-60-1.

Research into error recovery for sensory robots

Lee, M., Barnes, D. P., Hardy, N. (1985). Research into error recovery for sensory robots. Sensor Review, 5 (4), 194-197.

Knowledge based error recovery in industrial robots

M. H. Lee, D. P. Barnes, and N. W. Hardy. Knowledge based error recovery in industrial robots. In Proc. 8th. Int. Joint Conf. Artificial Intelligence, pages 824-826, Karlsruhe, FDR., 1983.

A control and monitoring system for multiple-sensor industrial robots

Barnes, D. P., Lee, M. H., Hardy, N. W. (1983). A control and monitoring system for multiple-sensor industrial robots. In Proc. 3rd. Int. Conf. Robot Vision and Sensory Controls, Cambridge, MA. USA., 471-479.