ISMCR 1994: Topical Workshop on Virtual Reality. Proceedings of the Fourth International Symposium on Measurement and Control in Robotics

This symposium on measurement and control in robotics included sessions on: (1) rendering, including tactile perception and applied virtual reality; (2) applications in simulated medical procedures and telerobotics; (3) tracking sensors in a virtual environment; (4) displays for virtual reality applications; (5) sensory feedback including a virtual environment application with partial gravity simulation; and (6) applications in education, entertainment, technical writing, and animation

Designing teachable robots

This thesis advances the design of teachable adaptable robots. I propose two paths of improvement to the popular, easy to use, leading method, in which a teacher literally leads the robot by its hand through movements. The improvements enable motor commands to be changed and conditional branches to be formed, without the need for a keyboard or other explicit programming device. On improvement path 1, the addition of a verbal correcting (VC) scheme would enable a teacher to make on-line verbal corrections to a robot's movement sequences. The further addition of a production system of corrections (PSC) would enable a robot to remember and use verbally taught conditional corrections. On path 2 a goal-seeking (GS) system and VC would enable a teacher to set goals, lead movements, and verbally correct the robot. The robot then selects its own motor commands for achieving goals. A multiple context learning system (MCLS), a multiple, extended GS system, combines the two paths. It enables both sequences and goals to be taught to a led robot. A simple, but real, led MCLS-robot is demonstrated. I establish four important properties of MCLSs: (a) an MCLS can enable a robot to learn to perform motor commands that are initially performed only by reflex, so that eye and speech motor commands, neither suitable for being led, can still be learned; (b) an MCLS can learn to be a Turing machine, which is a universal computing machine, explicitly showing the error in criticisms of MCLSs' computational power; (c) the selections of a context learning system in an MCLS converge on the optimal motor commands for achieving goals; and (d) an MCLS-robot can handle the negation problem; doing something positive in the absence of a certain condition

Stable, high-force, low-impedance robotic actuators for human-interactive machines

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 347-359).Robots that engage in significant physical interaction with humans, such as robotic physical therapy aids, must exhibit desired mechanical endpoint impedance while simultaneously producing large forces. In most practical robot configurations, this requires actuators with high force-to-weight ratios and low intrinsic impedance. This thesis explores several approaches to improve the tradeoff between actuator force capacity, weight, and ability to produce desired impedance. Existing actuators that render impedance accurately generally have poor force densities while those with high force densities often have high intrinsic impedance. Aggressive force feedback can reduce apparent endpoint impedance, but compromises coupled stability. The common standard for ensuring coupled stability, passivity, can limit performance severely. An alternative measure of coupled stability is proposed that uses limited knowledge of environment dynamics (e.g. a human limb) and applies robust stability tools to port functions. Because of structural differences between interaction control and servo control, classical single-input, single-output control tools cannot be directly applied for design. Instead, a search method is used to select controller parameters for an assumed structure.(cont.) Simulations and experiments show that this new approach can be used to design a force-feedback controller for a robot actuator that improves performance, reduces conservatism, and maintains coupled stability. Adding dynamics in series to change an actuator's physical behavior can also improve performance. The design tools developed for controller design are adapted to select parameters for physical series dynamics and the control system simultaneously. This design procedure is applied to both spring-damper and inertial series dynamics. Results show that both structures can be advantageous, and that the systematic design of hardware and control together can improve performance dramatically over prior work. A remote transmission design is proposed to reduce actuator weight directly. This design uses a stationary direct-drive electromagnetic actuator and a passive, flexible hydraulic transmission with low intrinsic impedance, thereby utilizing the impedance- rendering capabilities of direct-drive actuation and the force density of hydraulic actuation. The design, construction and characterization of a low-weight, low-friction prototype for a human arm therapy robot are discussed. Recommendations and tradeoffs are presented.by Stephen Paul Buerger.Ph.D

A Robot Operating System (ROS) based humanoid robot control

This thesis presents adapting techniques required to enhance the capability of a commercially available robot, namely, Robotis Bioloid Premium Humanoid Robot (BPHR). BeagleBone Black (BBB), the decision-making and implementing (intelligence providing) component, with multifunctional capabilities is used in this research. Robot operating System (ROS) and its libraries, as well as Python Script and its libraries have been developed and incorporated into the BBB. This fortified BBB intelligence providing component is then transplanted into the structure of the Robotis Bioloid humanoid robot, after removing the latter’s original decision-making and implementing component (controller). Thus, this study revitalizes the Bioloid humanoid robot by converting it into a humanoid robot with multiple features that can be inherited using ROS. This is a first of its kind approach wherein ROS is used as the development framework in conjunction with the main BBB controller and the software impregnated with Python libraries is used to integrate robotic functions. A full ROS computation is developed and a high level Application Programming Interface (API) usable by software utilizing ROS services is also developed. In this revised two-legged-humanoid robot, USB2Dynamixel connector is used to operate the Dynamixel AX-12A actuators through the Wi-Fi interface of the fortified BBB. An accelerometer sensor supports balancing of the robot, and updates data to the BBB periodically. An Infrared (IR) sensor is used to detect obstacles. This dynamic model is used to actuate the motors mounted on the robot leg thereby resulting in a swing-stance period of the legs for a stable forward movement of the robot. The maximum walking speed of the robot is 0.5 feet/second, beyond this limit the robot becomes unstable. The angle at which the robot leans is governed by the feedback from the accelerometer sensor, which is 20 degrees. If the robot tilts beyond a specific degree, then it would come back to its standstill position and stop further movement. When the robot moves forward, the IR sensors sense obstacles in front of the robot. If an obstacle is detected within 35 cm, then the robot stops moving further. Implementation of ROS on top of the BBB (by replacing CM530 controller with the BBB) and using feedback controls from the accelerometer and IR sensor to control the two-legged robotic movement are the novelties of this work

The design and intelligent control of an autonomous mobile robot

This thesis presents an investigation into the problems of exploration, map building and collision free navigation for intelligent autonomous mobile robots. The project began with an extensive review of currently available literature in the field of mobile robot research, which included intelligent control techniques and their application. It became clear that there was scope for further development with regard to map building and exploration in new and unstructured environments. Animals have an innate propensity to exhibit such abilities, and so the analogous use of artificial neural networks instead of actual neural systems was examined for use as a method of robot mapping. A simulated behaviour based mobile robot was used in conjunction with a growing cell structure neural network to map out new environments. When using the direct application of this algorithm, topological irregularities were observed to be the direct result of correlations within the input data stream. A modification to this basic system was shown to correct the problem, but further developments would be required to produce a generic solution. The mapping algorithms gained through this approach, although more similar to biological systems, are computationally inefficient in comparison to the methods which were subsequently developed. A novel mapping method was proposed based on the robot creating new location vectors, or nodes, when it exceeded a distance threshold from its mapped area. Network parameters were developed to monitor the state of growth of the network and aid the robot search process. In simulation, the combination of the novel mapping and search process were shown to be able to construct maps which could be subsequently used for collision free navigation. To develop greater insights into the control problem and to validate the simulation work the control structures were ported to a prototype mobile robot. The mobile robot was of circular construction, with a synchro-drive wheel configuration, and was equipped with eight ultrasonic distance sensors and an odometric positioning system. It was self-sufficient, incorporating all its power and computational resources. The experiments observed the effects of odometric drift and demonstrated methods of re-correction which were shown to be effective. Both the novel mapping method, and a new algorithm based on an exhaustive mesh search, were shown to be able to explore different environments and subsequently achieve collision free navigation. This was shown in all cases by monitoring the estimates in the positional error which remained within fixed bounds

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Autonomous vehicles that care for houseplants

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 91-95).Robotany is a system of autonomous robots that act on behalf of houseplants that rest on top of their chassis. Their duty is to do what plants would if they had the gift of mobility - namely to seek out sunlight or water when there are insufficient amounts of either at their current location. Despite the specialized application, the underlying framework of the robots is rather general and can be used in a variety of situations. The robots are designed to be easily modifiable for a given application. They are constructed using rapid-prototyping techniques that allow them to be built quickly and The software controlling Robotany utilizes a behavior-based approach, one that takes its cue from nature's solutions to problems facing any mobile being. It follows Braitenberg's model for seeking out light in an implicit manner. A new approach to obstacle avoidance is used, based on reactance to in situ sensor readings and a simplified internal map of the local environment. Robotany also incorporates a simple homeostatic system to regulate the quality of its behaviors and to determine when one behavior should take precedence over another. inexpensively. A novel design is utilized for the vehicle's suspension. This design is far simpler, cheaper, and more easily customized than traditional systems that perform the same task. The software controlling Robotany utilizes a behavior-based approach, one that takes its cue from nature's solutions to problems facing any mobile being. It follows Braitenberg's model for seeking out light in an implicit manner. A new approach to obstacle avoidance is used, based on reactance to in situ sensor readings and a simplified internal map of the local environment. Robotany also incorporates a simple homeostatic system to regulate the quality(cont.) of its behaviors and to determine when one behavior should take precedence over another. Experimental results presented in this thesis show that the robots are successful in finding sources of light while avoiding obstacles in their path.by Sara Elizabeth Cinnamon.S.M

Chess Robot

ME450 Capstone Design and Manufacturing Experience: Winter 2021The Chess Robot is designed to be an autonomous robotic arm that is able to compete in a chess match against a human. The robot moves their own pieces and captures the opponent’s pieces in efforts to win a standard game of chess. Robotic arms that play chess have been created before, but are either industrial grade and expensive or very cheap/homemade and slow. This project aimed to create a functional chess robot that maximizes speed at a relatively low cost. It was also designed with potential for mass manufacturing in mind. With additional design and development, the skill of the robot should be easily changed, since the software is easily customized; thus, as the player improves, so will the robot. There will also be an opportunity to play chess against other humans through two intermediary robots or for one player to play while making use of an online chess platform. This feature, if fully developed, will enable chess instructors to play with children and not be limited by geographical proximity, further expanding the reach of chess education.Student Sponsor: UM Mechanical Engineering departmenthttp://deepblue.lib.umich.edu/bitstream/2027.42/167650/1/Team_5-Chess_Robot.pd

Framework of active robot learning

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Master of Science by researchIn recent years, cognitive robots have become an attractive research area of Artificial Intelligent (AI). High-order beliefs for cognitive robots regard the robots' thought about their users' intention and preference. The existing approaches to the development of such beliefs through machine learning rely on particular social cues or specifically defined award functions . Therefore, their applications can be limited. This study carried out primary research on active robot learning (ARL) which facilitates a robot to develop high-order beliefs by actively collecting/discovering evidence it needs. The emphasis is on active learning, but not teaching. Hence, social cues and award functions are not necessary. In this study, the framework of ARL was developed. Fuzzy logic was employed in the framework for controlling robot and for identifying high-order beliefs. A simulation environment was set up where a human and a cognitive robot were modelled using MATLAB, and ARL was implemented through simulation. Simulations were also performed in this study where the human and the robot tried to jointly lift a stick and keep the stick level. The simulation results show that under the framework a robot is able to discover the evidence it needs to confirm its user's intention

Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot

Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming increasingly important as the level of play rises. Competition around the ball is now decided in a matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to kick the ball. It is common to see a discontinuity between walking and kicking where a robot will return to an initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour by developing a transition gait that morphs the walk directly into the kick back swing pose. The solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot. The solution we develop involves the design of a central pattern generator to allow for controlled steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk so that precise step length control can be activated when required. An open loop trajectory mapping approach is taken to the walk that is stabilized statically through the use of a phase varying joint holding torque technique. We also examine the basic princples of open loop walking, focussing on the commonly overlooked frontal plane motion. The act of kicking itself is explored both analytically and empirically, and solutions are provided that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour (process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate and efficient in terms of speed of execution