Multi-Robot Transfer Learning: A Dynamical System Perspective

Multi-robot transfer learning allows a robot to use data generated by a second, similar robot to improve its own behavior. The potential advantages are reducing the time of training and the unavoidable risks that exist during the training phase. Transfer learning algorithms aim to find an optimal transfer map between different robots. In this paper, we investigate, through a theoretical study of single-input single-output (SISO) systems, the properties of such optimal transfer maps. We first show that the optimal transfer learning map is, in general, a dynamic system. The main contribution of the paper is to provide an algorithm for determining the properties of this optimal dynamic map including its order and regressors (i.e., the variables it depends on). The proposed algorithm does not require detailed knowledge of the robots' dynamics, but relies on basic system properties easily obtainable through simple experimental tests. We validate the proposed algorithm experimentally through an example of transfer learning between two different quadrotor platforms. Experimental results show that an optimal dynamic map, with correct properties obtained from our proposed algorithm, achieves 60-70% reduction of transfer learning error compared to the cases when the data is directly transferred or transferred using an optimal static map.Comment: 7 pages, 6 figures, accepted at the 2017 IEEE/RSJ International Conference on Intelligent Robots and System

On the Construction of Safe Controllable Regions for Affine Systems with Applications to Robotics

This paper studies the problem of constructing in-block controllable (IBC) regions for affine systems. That is, we are concerned with constructing regions in the state space of affine systems such that all the states in the interior of the region are mutually accessible through the region's interior by applying uniformly bounded inputs. We first show that existing results for checking in-block controllability on given polytopic regions cannot be easily extended to address the question of constructing IBC regions. We then explore the geometry of the problem to provide a computationally efficient algorithm for constructing IBC regions. We also prove the soundness of the algorithm. We then use the proposed algorithm to construct safe speed profiles for different robotic systems, including fully-actuated robots, ground robots modeled as unicycles with acceleration limits, and unmanned aerial vehicles (UAVs). Finally, we present several experimental results on UAVs to verify the effectiveness of the proposed algorithm. For instance, we use the proposed algorithm for real-time collision avoidance for UAVs.Comment: 17 pages, 18 figures, under review for publication in Automatic

The effect of hydrogen on the magnetic properties of FeV superlattice

The electronic and magnetic structures of a hydrogenated and hydrogen free superlattice of 3 iron monolayers and 9 vanadium monolayers are studied using the first principle full-potential augmented-plane-wave method as implemented in WIEN2k package. The volume, the total energy and the magnetic moments of the system are studied versus the hydrogen positions at the octahedral sites within the superlattice and also versus the filling of the vanadium octahedral location by hydrogen atoms. It is found that the hydrogen locations at the interior of vanadium layer are energetically more favourable. The local Fe magnetic moment and the average magnetic moment per supercell are found to increase as the H position moves towards the Fe-V interface. On the other hand, the average magnetic moment per supercell is found to initially decrease up to filling by 3 H atoms and then increases afterwards. To our knowledge, this is the first reporting on the increase in the computed magnetic moment with hydrogenation. These trends of magnetic moments are attributed to the volume changes resulting from hydrogenation and not to electronic hydrogen-metal interaction.Comment: 13 pages, 5 figures and 2 table