Volume 1, Issue 3

This communication presents and justifies ideas related to motion control of snake robots that are currently the subject of ongoing investigations by the authors. In particular, we highlight requirements for intelligent and effcient snake robot locomotion in unstructured environments, and subsequently we present two new design concepts for snake robots that comply with these requirements. The first design concept is an approach for sensing environment contact forces, which is based on measuring the joint constraint forces at the connection between the links of the snake robot. The second design concept involves allowing the cylindrical surface of each link of a snake robot to rotate by a motor inside the link in order to induce propulsive forces on the robot from its environments. The paper details the advantages of the proposed design concepts over previous snake robot designs.

A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate the performance of the network and to train it on the examples for which they repeatedly fail, until all the examples are correctly classified. Empirical analysis on UCI data show that the algorithm produces good training data and improves the generalization ability of the network on unseen data. The algorithm has interesting applications in data mining, model evaluations and rare objects discovery.

The overarching goal of the FaceBots project is to support the achievement of sustainable long-term human-robot relationships through the creation of robots with face recognition and natural language capabilities, which exploit and publish online information, and especially social information available on Facebook, and which achieve two significant novelties. The underlying experimental hypothesis is that such relationships can be significantly enhanced if the human and the robot are gradually creating a pool of episodic memories that they can co-refer to (“shared memories”), and if they are both embedded in a social web of other humans and robots they mutually know (“shared friends”). We present a description of system architecture, as well as important concrete results regarding face recognition and transferability of training, with training and testing sets coming from either one or a combination of two sources: an onboard camera which can provide sequences of images, as well as facebook-derived photos. Furthermore, early interaction-related results are presented, and evaluation methodologies as well as interesting extensions are discussed.

We have developed a new simulation environment, called N eu V ision , that is able to perform neuro-robotic experiments in a closed-loop architecture, by simulating a large-scale neuronal network bi-directionally connected to a robot. We conceived it primarily as a support tool to be used in the context of the ‘embodied electrophysiology’, a growing field that could help, in the future, to realize innovative bi-directional and adaptive Brain-Machine Interfaces. The main features of our system are related to the efficient visualization of the neural activity, the possibility to define different connectivity rules and stimulation points, and the integration of statistical analysis tools for fast neural dynamics characterization. Our preliminary results show that we are able to reproduce both spontaneous and evoked activity of cultured networks. Hence, by defining a decoding strategy based on the Center of Activity, we carried out experiments with a simulated neuronal network in a closed-loop with a robot. Our results suggest the N eu V ision simulated environment could be used as a tool to support in vitro experiments with real systems.

Snake-like robots have gained popularity in the last three decades for their ability to utilize several gaits in order to navigate through different terrains. They are analogous in morphology to snakes, tentacles, and elephant trunks. We propose a novel method of navigating a snake-like robot based on the Harmonic Field with Optimized Boundary Conditions (HFOBC) and a boundary following algorithm. We apply the HFOBC navigation function using a number of fictitious charges equally spaced on each link. These charges actively follow the potential field towards the target. Futhermore, a generalized mathematical model for an n-link snake-like robot based on Lagrange formulation has also been proposed in this paper.