Drosophila germ cell migration is directed by attractive and repulsive guidance cues. We have identified a novel gene, slow as molasses (slam), which is required for germ cell migration. In slam zygotic mutants, germ cells fail to transit off the midgut into the mesoderm. We show that slam is required at this stage in parallel to HMG Coenzyme A reductase, a previously identified germ cell migra...

Simultaneous localization and mapping (SLAM) is a prominent feature for autonomous robots operating in undefined environments. Applications areas such as consumer robotics appliances would clearly benefit from low-cost and compact SLAM implementations. The SLAM research community has developed several robust algorithms in the course of the last two decades. However, until now most SLAM demonstr...

This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lowerd...

This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lowerd...

Simultaneous Localization and Mapping (SLAM) is the basis for autonomous navigation of underwater vehicles, and main solution to SLAM is based on extended Kalman filter (EKF). In order to obtain a more precise trajectory and map result, this paper describes a SLAM approach, which combines SLAM theory with other sensors update to locate and map for robot, namely not only adopts sonar information...

This paper presents a new generalisation of simultaneous localisation and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriag...

Recently, a novel laser data based SLAM algorithm using B-Spline as features has been developed in [Pedraza et al., 2007]. EKF is used in the proposed BS-SLAM algorithm and the state vector contains the current robot pose together with the control points of the splines. The obervation model used for the EKF update is the intersections of the laser beams with the splines contained in the map. In...

This paper proposes a novel approach to an RGB-D simultaneous localization and mapping (SLAM) system that uses the vanishing point and door plates in a corridor environment simultaneously for navigation. To increase the stability of the SLAM process in such an environment, the vanishing point and door plates are utilized as landmarks for extended Kalman filterbased SLAM (i.e., EKF SLAM). The va...

Simultaneous Localization and Mapping (SLAM) has been one of the active research areas in robotic community for the past decade of years. SLAM addresses the problem of a robot navigating and building a map of an unknown environment, without an initial map or an absolute localization means. This paper attempts to provide a comprehensive overview of the SLAM problem. Successful SLAM implementatio...

The problem of determining the pose (position and orientation) of a sensor in an unknown environment by incrementally building up a map of the environment is known as Simultaneous Localisation and Mapping (SLAM) in robotics. Currently, the focus for SLAM work has been done on sensors such as laser rangefinders and sonar with very little work on using vision as a sensor. This paper investigates ...