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Robotic devices are increasingly penetrating the human work spaces as stand alone units and helpers. It is believed that a robot could be easily integrated with humans, if the robot can learn how to behave in a socially acceptable manner. This involves a robot to observe, learn and comply with basic rules of human behaviors. As an example, one would expect a robot to travel in an environment without...
Human robot interaction is an emerging area of research, where human understandable robotic representations can play a major role. Knowledge of semantic labels of places can be used to effectively communicate with people and to develop efficient navigation solutions in complex environments. In this paper, we propose a new approach that enables a robot to learn and classify observations in an indoor...
Extending metric space representations of an environment with other high level information, such as semantic and topological representations enable a robotic device to efficiently operate in complex environments. This paper proposes a methodology for a robot to classify indoor environments into semantic categories. Classification task, using data collected from a laser range finder, is achieved by...
Human robot interaction is an emerging area of research with many challenges. Knowledge about human behaviors could lead to more effective and efficient interactions of a robot in populated environments. This paper presents a probabilistic framework for the learning and representation of human motion patterns in an office environment. It is based on the observation that most human trajectories are...
The main contribution of this paper is a mathematical model describing performance metrics for coordinating multiple mobile robots in a seaport container terminal. The scenario described here requires dealing with many difficult practical challenges such as the presence of multiple levels of container stacking and sequencing, variable container orientations, and vehicular dynamics that require finite...
A mechanism capable of enhancing the safety of paths followed by mobile robots which significantly modify their mass distribution while operating in uneven terrains is presented. This is the case, for instance, of kinematically reconfigurable platforms or robots equipped with manipulator arms. For a given path, a trajectory optimiser that finds suitably ??safer?? paths in terms of tip-over prevention...
When autonomous vehicles are deployed to perform transportation tasks within a confined space and strict time constraint, the problem of optimizing the assignment of tasks to vehicles is complicated by the need to ensure safety (they do not collide with or impede each other) and maximize the efficiency and productivity. With the increasing number of autonomous vehicles in practical settings, the ability...
This paper presents an intelligent decision-making agent to assist wheelchair users in their daily navigation activities. Several navigational techniques have been successfully developed in the past to assist with specific behaviours such as "door passing" or "corridor following". These shared control strategies normally require the user to manually select the level of assistance...
This paper considers the trajectory planning problem for line-feature based SLAM in structured indoor environments. The robot poses and line features are estimated using smooth and mapping (SAM) which is found to provide more consistent estimates than the extended Kalman filter (EKF) The objective of trajectory planning is to minimise the uncertainty of the estimates and to maximise coverage. Trajectory...
A problem of searching with multiple searchers and scouts is presented. Unlike most search problems that terminate as soon as the target is found, successful detection by scouts only improve on the current knowledge of the moving target's location, such that the searchers can more effectively find and service the target in the future. The team must correspondingly plan not only to maximize the probability...
This paper proposes a optimal control method for simultaneous localisation and mapping (SLAM) in an indoor environment using stereo vision. Specially designed artificial landmarks distributed in the environment are observed and extracted from a camera image. The disparity map obtained from the stereo vision system is used to obtain the ranges to these landmarks. The main contribution of the paper...
With the increasing applications of fully autonomous vehicles, efficient motion coordination of multi-autonomous vehicles becomes a very important problem as it significantly affects the productivity. This problem is even harder to solve with the increases of the number of autonomous vehicles employed in a dynamic changing environment and constraints to vehicle movement. This paper presents a simultaneous...
This paper applies a meta-heuristic based ant colony optimization (ACO) technique for simultaneous task allocation and path planning of automated guided vehicles (AGV) in material handling. ACO algorithm allocates tasks to AGVs based on collision free path obtained by a proposed path and motion planning algorithm. The validity of this approach is investigated by applying it to different task and AGV...
Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, and the dynamic and motion constraints need to be considered in the planning process. In this paper, the active SLAM problem is formulated as an optimal trajectory planning problem. A novel technique is introduced that utilises...
The main contribution of this paper is a theoretical analysis of the extended Kalman filter (EKF) based solution to the simultaneous localisation and mapping (SLAM) problem. The convergence properties for the general nonlinear two-dimensional SLAM are provided. The proofs clearly show that the robot orientation error has a significant effect on the limit and/or the lower bound of the uncertainty of...
The main contribution of this paper is a new SLAM algorithm for the mapping of large scale environments by combining local maps. The local maps can be generated by traditional extended Kalman filter (EKF) based SLAM. Relationships between the locations of the landmarks in the local map are then extracted and used in an extended information filter (EIF) to build a global map. An important feature is...
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