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Posted on: July 19, 2012
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Providing adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This study aims at real-time differentiation between fast and slow trials in a motor imagery BCI. In our experiments, we refer to trials shorter than the median of trial lengths as “fast” trials and to those longer than the median as “slow” trials. We propose a classifier for real-time distinction between fast and slow trials based on estimates of the entropy rates for the first 2-3 s of the electroencephalogram (EEG). Results suggest that it can be predicted whether a trial is slow or fast well before a cutoff time. This is important for adaptive shared control especially because 55% to 75% of trials (for the five subjects in this study) are longer than that cutoff time
Posted on: July 16, 2012
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We present the design and evaluation of an iPad application that will be used to operate the modular robots “Roombots”. Roombots are the building blocks for adaptive pieces of furniture. The application allows a user to arrange adaptive furniture within a room. We conducted a user study with 24 participants to evaluate our approach and to freely explore people’s interaction. Data suggests that the ability to move with the device leads to a better precision of the furniture arrangement. No significant difference has been observed between using the application through a virtual representation of the room in contrast to an augmented reality environment, even if participants mentioned in a post-study questionnaire their preference for the augmented condition. Users described the interface as intuitive and easy to use.
Posted on: July 10, 2012
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A single leg hopping robot has been constructed which includes a clutch in series with the hip motor and a prototype Linear Multi-Modal Actuator (LMMA) at the knee. The single leg will be used to test how the different actuation methods can improve the behavioural diversity of the robot.
Posted on: June 28, 2012
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Recent results in spinal research are challenging the historical view that the spinal reflexes are mostly hardwired and fixed behaviours. In previous work we have shown that three of the simplest spinal reflexes could be self-organised in an agonist-antagonist pair of muscles. The simplicity of these reflexes is given from the fact that they entail at most one interneuron mediating the connectivity between afferent inputs and efferent outputs. These reflexes are: the Myotatic, the Reciprocal Inibition and the Reverse Myotatic reflexes. In this paper we apply our framework to a simulated 2D leg model actuated by six muscles (mono- and bi-articular). Our results show that the framework is successful in learning most of the spinal reflex circuitry as well as the corresponding behaviour in the more complicated muscle arrangement.
Posted on: June 28, 2012
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There has been a long-standing debate on the question of how basic reflexive behaviours in mammals come about. Recently, it has been hypothesized that soft musculoskeletal interactions, such as intrinsic passive dynamics, might play a crucial role in the development of motor control at an early developmental stage. Inspired by the developmental processes, this paper explores a learning framework that enables us to systematically investigate the sensorimotor activity induced in soft musculoskeletal systems, as well as to self-organize a set of decentralized controllers analogue to spinal reflexes in mammals. This paper particularly focuses on three reflexes: the Myotatic reflex, the Reciprocal Inhibition reflex and the Reverse Myotatic reflex. We tested our framework in a simulated pair of soft muscles assembled in an agonist-antagonist arrangement. Our results show that the reflex circuitry as well as the reflex behaviour obtained are consistent with those observed in the mammal spinal cord.
Posted on: June 28, 2012
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Most of the conventional legged robots are based on rigid body parts connected by high-torque actuators and a sophisticated control scheme to achieve stable running locomotion. The energy-efficiency of such robots is roughly 10-100 times lower than that of animals. Recently, there has been an increasing interest in designing compliant robots which exploit body dynamics for adaptive locomotion. It was shown that freevibration of elastic mechanical structures can generate energyefficient hopping/walking behavior. However, the velocity of such robots is very low. From this perspective, this paper presents a novel design strategy for running robots which makes use of torsional vibration of elastic beam. We propose a simple physical model which can be used to obtain the resonance frequency of the robot during stance phase. Moreover, this model can represent the dynamic behavior of such a robot during running locomotion.
Posted on: June 28, 2012
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Behavioral performances of our legged robots are still far behind those of biological systems. Energy efficiency and locomotion velocity of our robots, for example, are orders of magnitude lower than those of animals, and in order to fill the gap, it requires a radically new approach in the design and control processes. From this perspective, we have been exploring a novel approach to design and control of legged robots which makes use of free vibration of elastic curved beams. We found that this approach not only simplifies the design and manufacturing processes of locomotion robots, but also substantially improves their energy efficiency, which is comparable to those of animals. In this paper, we explain the novelty and principles of this approach through the four representative case studies that we have been exploring, and discuss challenges and perspectives toward the future. © 2012 IEEE.
Posted on: June 28, 2012
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Posted on: June 28, 2012
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There has been an increasing interest in the use of unconventional materials and morphologies in robotic systems because the underlying mechanical properties (such as body shapes, elasticity, viscosity, softness, density and stickiness) are crucial research topics for our in-depth understanding of embodied intelligence. The detailed investigations of physical system-environment interactions are particularly important for systematic development of technologies and theories of emergent adaptive behaviors. Based on the presentations and discussion in the Future Emerging Technology (fet11) conference, this article introduces the recent technological development in the field of soft robotics, and speculates about the implications and challenges in the robotics and embodied intelligence research. (C) Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V.
Posted on: June 28, 2012
