Efficient Model Learning for Human-Robot Collaborative Tasks

We present a framework for learning human user models from joint-action demonstrations that enables the robot to compute a robust policy for a collaborative task with a human. The learning takes place completely automatically, without any human intervention. First, we describe the clustering of demonstrated action sequences into different human types using an unsupervised learning algorithm. These demonstrated sequences are also used by the robot to learn a reward function that is representative for each type, through the employment of an inverse reinforcement learning algorithm. The learned model is then used as part of a Mixed Observability Markov Decision Process formulation, wherein the human type is a partially observable variable. With this framework, we can infer, either offline or online, the human type of a new user that was not included in the training set, and can compute a policy for the robot that will be aligned to the preference of this new user and will be robust to deviations of the human actions from prior demonstrations. Finally we validate the approach using data collected in human subject experiments, and conduct proof-of-concept demonstrations in which a person performs a collaborative task with a small industrial robot

Palladium(II) complexes of tridentate bis(benzazole) ligands: Structural, substitution kinetics, DNA interactions and cytotoxicity studies.

Reactions of 2,6-bis(benzimidazol-2-yl)pyridine (L1), 2,6-bis(benzoxazol-2-yl)pyridine (L2), and 2,6-bis(benzothiazol-2-yl)pyridine (L3) with [Pd(NCMe)2Cl2] in the presence of NaBF4 afforded the corresponding Pd(II) complexes, [Pd(L1)Cl]BF4, PdL1; [Pd(L2)Cl]BF4, PdL2; [Pd(L3)Cl]BF4, PdL3; respectively, while reaction of bis[(1H-benzimidazol-2-yl)methyl]amine (L4) with [Pd(NCMe)2Cl2] afforded complex [Pd(L4)Cl]Cl, PdL4. Characterisation of the complexes was accomplished using NMR, IR, MS, elemental analyses and single crystal X-ray crystallography. Ligand substitution kinetics of these complexes by biological nucleophiles thiourea (Tu), L-methionine (L-Met) and guanosine 5'-diphosphate disodium salt (5-GMP) were examined under pseudo-first order conditions. The reactivity of the complexes decreased in the order: PdL1 > PdL2 > PdL3 > PdL4, ascribed to electronic effects. Density functional theory (DFT) supported this trend. Studies of interaction of the Pd(II) complexes with calf thymus DNA (CT-DNA) revealed strong binding affinities via intercalative binding mode. Molecular docking studies established associative non-covalent interactions between the Pd complexes and DNA. The in vitro cytotoxic activities of PdL1-PdL4 were assessed in cancer cell lines HeLa and MRC5-SV2 and a normal cell line MRC-5, using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. PdL1 exhibited cytotoxic potency and selectivity against HeLa cell that was comparable to cisplatin's. Complex PdL1, unlike cisplatin, did not significantly induce caspase-dependent apoptosis

Designworld: an augmented 3D virtual world for multidisciplinary, collaborative design

Large design projects, such as those in the AEC domain, involve collaboration between designers from many different design disciplines in varying locations. Existing tools for developing and documenting designs of buildings and other artifacts tend to focus on supporting a single user from a single discipline. This paper introduces DesignWorld, a prototype system for enabling collaboration between designers from different disciplines who may be in different physical locations. DesignWorld consists of a 3D virtual world augmented with a number of web-based communication and design tools. DesignWorld uses agent technology to maintain different views of a single design in order to support multidisciplinary collaboration and address issues such as multiple representations of objects, versioning, ownership and relationships between objects from different disciplines.