Improved Dynamic Obstacle Mapping (iDOMap).

The goal of this paper is to improve our previous Dynamic Obstacle Mapping (DOMap) system by means of improving the perception stage. The new system must deal with robots and people as dynamic obstacles using LIght Detection And Range (LIDAR) sensor in order to collect the surrounding information. Although robot movement can be easily tracked by an Extended Kalman Filter (EKF), people's movement is more unpredictable and it might not be correctly linearized by an EKF. Therefore, to deal with a better estimation of both types of dynamic objects in the local map it is recommended to improve our previous work. The DOMap has been extended in three key points: first the LIDAR reflectivity remission is used to make more robust the matching in the optical flow of the detection stage, secondly static and a dynamic occlusion detectors have been proposed, and finally a tracking stage based on Particle Filter (PF) has been used to deal with robots and people as dynamic obstacles. Therefore, our new improved-DOMap (iDOMap) provides maps with information about occupancy and velocities of the surrounding dynamic obstacles (robots, people, etc.) in a more robust way and they are available to improve the following planning stage.

A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments.

One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory configuration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF. When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control.

Dynamic obstacle avoidance using Bayesian Occupancy Filter and approximate inference.

The goal of this paper is to solve the problem of dynamic obstacle avoidance for a mobile platform using the stochastic optimal control framework to compute paths that are optimal in terms of safety and energy efficiency under constraints. We propose a three-dimensional extension of the Bayesian Occupancy Filter (BOF) (Coué et al. Int. J. Rob. Res. 2006, 25, 19-30) to deal with the noise in the sensor data, improving the perception stage. We reduce the computational cost of the perception stage by estimating the velocity of each obstacle using optical flow tracking and blob filtering. While several obstacle avoidance systems have been presented in the literature addressing safety and optimality of the robot motion separately, we have applied the approximate inference framework to this problem to combine multiple goals, constraints and priors in a structured way. It is important to remark that the problem involves obstacles that can be moving, therefore classical techniques based on reactive control are not optimal from the point of view of energy consumption. Some experimental results, including comparisons against classical algorithms that highlight the advantages, are presented.

Cationic rhodium mono-phosphine fragments partnered with carborane monoanions [closo-CB11H6X6]- (X = H, Br). Synthesis, structures and reactivity with alkenes.

Addition of the new phosphonium carborane salts [HPR(3)][closo-CB(11)H(6)X(6)] (R = (i)Pr, Cy, Cyp; X = H 1a-c, X = Br 2a-c; Cy = C(6)H(11), Cyp = C(5)H(9)) to [Rh(nbd)(mu-OMe)](2) under a H(2) atmosphere gives the complexes Rh(PR(3))H(2)(closo-CB(11)H(12)) 3 (R = (i)Pr 3a, Cy 3b, Cyp 3c) and Rh(PR(3))H(2)(closo-CB(11)H(6)Br(6)) 4 (R = (i)Pr 4a, Cy 4b, Cyp 4c). These complexes have been characterised spectroscopically, and for 4b by single crystal X-ray crystallography. These data show that the {Rh(PR(3))H(2)}(+) fragment is interacting with the lower hemisphere of the [closo-CB(11)H(6)X(6)](-) anion on the NMR timescale, through three Rh-H-B or Rh-Br interactions for complexes 3 and 4 respectively. The metal fragment is fluxional over the lower surface of the cage anion, and mechanisms for this process are discussed. Complexes 3a-c are only stable under an atmosphere of H(2). Removing this, or placing under a vacuum, results in H(2) loss and the formation of the dimer species Rh(2)(PR(3))(2)(closo-CB(11)H(12))(2) 5a (R = (i)Pr), 5b (R = Cy), 5c (R = Cyp). These dimers have been characterised spectroscopically and for 5b by X-ray diffraction. The solid state structure shows a dimer with two closely associated carborane monoanions surrounding a [Rh(2)(PCy(3))(2)](2+) core. One carborane interacts with the metal core through three Rh-H-B bonds, while the other interacts through two Rh-H-B bonds and a direct Rh-B link. The electronic structure of this molecule is best described as having a dative Rh(I) --> Rh(III), d(8)--> d(6), interaction and a formal electron count of 16 and 18 electrons for the two rhodium centres respectively. Addition of H(2) to complexes 5a-c regenerate 3a-c. Addition of alkene (ethene or 1-hexene) to 5a-c or 3a-c results in dehydrogenative borylation, with 1, 2, and 3-B-vinyl substituted cages observed by ESI-MS: [closo-(RHC[double bond, length as m-dash]CH)(x)CB(11)H(12-x)](-)x = 1-3, R = H, C(4)H(9). Addition of H(2) to this mixture converts the B-vinyl groups to B-ethyl; while sequential addition of 4 cycles of ethene (excess) and H(2) to CH(2)Cl(2) solutions of 5a-c results in multiple substitution of the cage (as measured by ESI-MS), with an approximately Gaussian distribution between 3 and 9 substitutions. Compositionally pure material was not obtained. Complexes 4a-c do not lose H(2). Addition of tert-butylethene (tbe) to 4a gives the new complex Rh(P(i)Pr(3))(eta(2)-H(2)C=CH(t)Bu)(closo-CB(11)H(6)Br(6)) 6, characterised spectroscopically and by X-ray diffraction, which show coordination of the alkene ligand and bidentate coordination of the [closo-CB(11)H(6)Br(6)](-) anion. By contrast, addition of tbe to 4b or 4c results in transfer dehydrogenation to give the rhodium complexes Rh{PCy(2)(eta(2)-C(6)H(9))}(closo-CB(11)H(6)Br(6)) 7 and Rh{PCyp(2)(eta(2)-C(5)H(7))}(closo-CB(11)H(6)Br(6)) 9, which contain phosphine-alkene ligands. Complex has been characterised crystallographically.

Polyethyl substituted weakly coordinating carborane anions: a sequential dehydrogenative borylation-hydrogenation route.

Polyethylated carborane monoanions based on [closo-CB11H12]- with up to five B-ethyl groups can be prepared by a sequential Rh-catalysed dehydrogenative borylation then hydrogenation.