Exploiting body dynamics for controlling a running quadruped robot

Exploiting the body dynamics to control the behavior of robots is one of the most challenging issues, because the use of body dynamics has a significant potential in order to enhance both complexity of the robot design and the speed of movement. In this paper, we explore the control strategy of rapid four-legged locomotion by exploiting the intrinsic body dynamics. Based on the fact that a simple model of four-legged robot is known to exhibit interesting locomotion behavior, this paper analyzes the characteristics of the dynamic locomotion for the purpose of the locomotion control. The results from a series of running experiments with a robot show that, by exploiting the unique characteristics induced by the body dynamics, the forward velocity can be controlled by using a very simple method, in which only one control parameter is required. Furthermore it is also shown that a few of such different control parameters exist, each of them can control the forward velocity. Interestingly, with these parameters, the robot exhibits qualitatively different behavior during the locomotion, which could lead to our comprehensive understanding toward the behavioral diversity of adaptive robotic systems. © 2005 IEEE.

Biologically inspired visual odometer for navigation of a flying robot

Experimental research in biology has uncovered a number of different ways in which flying insects use cues derived from optical flow for navigational purposes, such as safe landing, obstacle avoidance and dead reckoning. In this study, we use a synthetic methodology to gain additional insights into the navigation behavior of bees. Specifically, we focus on the mechanisms of course stabilization behavior and visually mediated odometer by using a biological model of motion detector for the purpose of long-range goal-directed navigation in 3D environment. The performance tests of the proposed navigation method are conducted by using a blimp-type flying robot platform in uncontrolled indoor environments. The result shows that the proposed mechanism can be used for goal-directed navigation. Further analysis is also conducted in order to enhance the navigation performance of autonomous aerial vehicles. © 2003 Elsevier B.V. All rights reserved.

Design and control of a pendulum driven hopping robot

In this paper a new kind of hopping robot has been designed which uses inverse pendulum dynamics to induce bipedal hopping gaits. Its mechanical structure consists of a rigid inverted T-shape mounted on four compliant feet. An upright "T" structure is connected to this by a rotary joint. The horizontal beam of the upright "T" is connected to the vertical beam by a second rotary joint. Using this two degree of freedom mechanical structure, with simple reactive control, the robot is able to perform hopping, walking and running gaits. During walking, it is experimentally shown that the robot can move in a straight line, reverse direction and control its turning radius. The results show that such a simple but versatile robot displays stable locomotion and can be viable for practical applications on uneven terrain.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.

Design and path planning for a remote-brained service robot

This paper presents a novel robot named "TUT03-A" with expert systems, speech interaction, vision systems etc. based on remote-brained approach. The robot is designed to have the brain and body separated. There is a cerebellum in the body. The brain with the expert systems is in charge of decision and the cerebellum control motion of the body. The brain-body. interface has many kinds of structure. It enables a brain to control one or more cerebellums. The brain controls all modules in the system and coordinates their work. The framework of the robot allows us to carry out different kinds of robotics research in an environment that can be shared and inherited over generations. Then we discuss the path planning method for the robot based on ant colony algorithm. The mathematical model is established and the algorithm is achieved with the Starlogo simulating environment. The simulation result shows that it has strong robustness and eligible pathfinding efficiency.

Design and path planning for a remote-brained service robot

This article introduced an effective design method of robot called remote-brain, which is made the brain and body separated. It leaves the brain in the mother environment, by which we mean the environment in which the brain's software is developed, and talks with its body by wireless links. It also presents a real robot TUT06-B based on this method which has human-machine interaction, vision systems, manipulator etc. Then it discussed the path planning method for the robot based on ant colony algorithm in details, especially the Ant-cycle model. And it also analyzed the parameter of the algorithm which can affect the convergence. Finally, it gives the program flow chat of this algorithm.

Large depth-of-view portable three-dimensional laser scanner and its segmental calibration for robot vision

A portable 3D laser scanning system has been designed and built for robot vision. By tilting the charge coupled device (CCD) plane of portable 3D scanning system according to the Scheimpflug condition, the depth-of-view is successfully extended from less than 40 to 100 mm. Based on the tilted camera model, the traditional two-step camera calibration method is modified by introducing the angle factor. Meanwhile, a novel segmental calibration approach, i.e., dividing the whole work range into two parts and calibrating, respectively, with corresponding system parameters, is proposed to effectively improve the measurement accuracy of the large depth-of-view 3D laser scanner. In the process of 3D reconstruction, different calibration parameters are used to transform the 2D coordinates into 3D coordinates according to the different positions of the image in the CCD plane, and the measurement accuracy of 60 mu m is obtained experimentally. Finally, the experiment of scanning a lamina by the large depth-of-view portable 3D laser scanner used by an industrial robot IRB 4400 is also employed to demonstrate the effectiveness and high measurement accuracy of our scanning system. (C) 2007 Elsevier Ltd. All rights reserved.

An Obstacle Cluster Based Data Fusion Method for Mobile Robot

首先给出了一种通过融合多个超声波传感器和一台激光全局定位系统的数据建立机器人环境地图的方法 ,并在此基础上 ,首次提出了机器人在非结构环境下识别障碍物的一种新方法 ,即基于障碍物群的方法 .该方法的最大特点在于它可以更加简洁、有效地提取和描述机器人的环境特征 ,这对于较好地实现机器人的导航、避障 ,提高系统的自主性和实时性是至关重要的 .大量的实验结果表明了该方法的有效性 .

A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network

Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical problems have been ignored.

Olympic Robot Building Manual

The 1989 AI Lab Winter Olympics will take a slightly different twist from previous Olympiads. Although there will still be a dozen or so athletic competitions, the annual talent show finale will now be a display not of human talent, but of robot talent. Spurred on by the question, "Why aren't there more robots running around the AI Lab?", Olympic Robot Building is an attempt to teach everyone how to build a robot and get them started. Robot kits will be given out the last week of classes before the Christmas break and teams have until the Robot Talent Show, January 27th, to build a machine that intelligently connects perception to action. There is no constraint on what can be built; participants are free to pick their own problems and solution implementations. As Olympic Robot Building is purposefully a talent show, there is no particular obstacle course to be traversed or specific feat to be demonstrated. The hope is that this format will promote creativity, freedom and imagination. This manual provides a guide to overcoming all the practical problems in building things. What follows are tutorials on the components supplied in the kits: a microprocessor circuit "brain", a variety of sensors and motors, a mechanical building block system, a complete software development environment, some example robots and a few tips on debugging and prototyping. Parts given out in the kits can be used, ignored or supplemented, as the kits are designed primarily to overcome the intertia of getting started. If all goes well, then come February, there should be all kinds of new members running around the AI Lab!

Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators

This thesis presents methods for implementing robust hexpod locomotion on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degrees of freedom, and 8 on board computers. We investigate the following topics in depth: distributed control of a complex robot, insect-inspired locomotion control for gait generation and rough terrain mobility, and fault tolerance. The controller was implemented, debugged, and tested on Hannibal. Through a series of experiments, we examined Hannibal's gait generation, rough terrain locomotion, and fault tolerance performance. These results demonstrate that Hannibal exhibits robust, flexible, real-time locomotion over a variety of terrain and tolerates a multitude of hardware failures.

Error Detection and Recovery for Robot Motion Planning with Uncertainty

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions.