Trajectory planning for multiple robots in bearing-only target localisation

This paper provides a solution to the optimal trajectory planning problem in target localisation for multiple heterogeneous robots with bearing-only sensors. The objective here is to find robot trajectories that maximise the accuracy of the locations of the targets at a prescribed terminal time. The trajectory planning is formulated as an optimal control problem for a nonlinear system with a gradually identified model and then solved using nonlinear Model Predictive Control (MPC). The solution to the MPC optimisation problem is computed through Exhaustive Expansion Tree Search (EETS) plus Sequential Quadratic Programming (SQP). Simulations were conducted using the proposed methods. Results show that EETS alone performs considerably faster than EETS+SQP with only minor differences in information gain, and that a centralised approach outperforms a decentralised one in terms of information gain. We show that a centralised EETS provides a near optimal solution. We also demonstrate the significance of using a matrix to represent the information gathered. © 2005 IEEE

Decentralized receding horizon control with application to multiple vehicle systems

Receding horizon control (RHC) has been one of the most popular control approaches recently due to its capability to achieve optimal performance in the presence of saturation constraints. There have been numerous new research results for RHC (also referred to as model predictive control) in the process control community. However, due to the high computational cost, associated with the numerical optimization problem, RHC has not often been successfully implemented on multiple vehicle systems with fast dynamics. Decentralized receding horizon control (DRHC) is a new promising approach to reduce the computational burden of RHC. It allows the division of the computation problem into smaller parts which are solved using a group of computational nodes. This results in a substantial reduction in the computational time required for RHC. This thesis involves modeling of wheeled and hovercraft vehicles including actuator dynamics. It then applies the DRHC approach to the vehicles and implements the DRHC systems in virtual reality simulations and an experimental setup. Together, these results establish a new and useful framework for applying RHC to multiple vehicle problems

Task Allocation Strategies in Multi-Robot Environment

Multirobot systems (MRS) hold the promise of improved performance and increased fault tolerance for large-scale problems. A robot team can accomplish a given task more quickly than a single agent by executing them concurrently. A team can also make effective use of specialists designed for a single purpose rather than requiring that a single robot be a generalist. Multirobot coordination, however, is a complex problem. An empirical study is described in the thesis that sought general guidelines for task allocation strategies. Different strategies are identified, and demonstrated in the multi-robot environment.Robot selection is one of the critical issues in the design of robotic workcells. Robot selection for an application is generally done based on experience, intuition and at most using the kinematic considerations like workspace, manipulability, etc. This problem has become more difficult in recent years due to increasing complexity, available features, and facilities offered by different robotic products. A systematic procedure is developed for selection of robot manipulators based on their different pertinent attributes. The robot selection procedure allows rapid convergence from a very large number of candidate robots to a manageable shortlist of potentially suitable robots. Subsequently, the selection procedure proceeds to rank the alternatives in the shortlist by employing different attributes based specification methods. This is an attempt to create exhaustive procedure by identifying maximum possible number of attributes for robot manipulators.Availability of large number of robot configurations has made the robot workcell designers think over the issue of selecting the most suitable one for a given set of operations. The process of selection of the appropriate kind of robot must consider the various attributes of the robot manipulator in conjunction with the requirement of the various operations for accomplishing the task. The present work is an attempt to develop a systematic procedure for selection of robot based on an integrated model encompassing the manipulator attributes and manipulator requirements