Muhammad Tahir Khan

Developments in Visual Servoing for Mobile Manipulation

A new trend in mobile robotics is to integrate visual information in feedback control for facilitating autonomous grasping and manipulation. The result is a visual servo system, which is quite beneficial in autonomous mobile manipulation. In view of mobility, it has wider application than the traditional visual servoing in manipulators with fixed base. In this paper, the state of art of vision-guided robotic applications is presented along with the associated hardware. Next, two classical approaches of visual servoing: image-based visual servoing (IBVS) and position-based visual servoing (PBVS) are reviewed; and their advantages and drawbacks in applying to a mobile manipulation system are discussed. A general concept of modeling a visual servo system is demonstrated. Some challenges in developing visual servo systems are discussed. Finally, a practical application of mobile manipulation system which is developed for applications of search and rescue and homecare robotics is introduced.

Autonomous fault tolerant multi-robot cooperation using artificial immune system

Multi-robot cooperation is an active research field where researchers have proposed different cooperation strategies. However, most of them have not considered fault tolerance, which will be critical when one or more robots fail during cooperation. In this paper we propose a self regulated fault tolerant multi-robot cooperation system based on the principles of artificial immune systems. The proposed approach relies on broadcasting of the capability and cost function of a robot that is required for cooperation while also taking care of partial and full failure of a robot during the communication for cooperation. In our system, a robot is regarded as an antibody and its environment as an antigen. The communication and cooperation strategies are inspired by Jernpsilas idiotypic network theory and the structure of the antibody. The developed methodology is verified by simulation.

Autonomous fault tolerant multi-robot coordination for object transportation based on Artificial Immune System

An efficient coordination strategy is required in order to realize an efficient and autonomous multi-robot cooperative system. This paper presents an approach for coordination among robots prior to cooperative object transportation. This paper does not address the coordination that is required during cooperation, which has been researched by others. In the present paper, fault tolerant coordination is achieved using methodology of artificial immune system. The approach developed here is based on binding affinity between an antibody and an antigen, and the structure of antibody in a human immune system. The developed methodology is verified through physical experiments.

Performance analysis of a semiactive suspension system with particle swarm optimization and fuzzy logic control.

This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control.

Immune System-Inspired Dynamic Multi-Robot Coordination

This paper investigates multi-robot coordination for the deployment of autonomous mobile robots in order to carry out a specific task. A key to utilizing of the full potential of cooperative multi-robot systems is effective and efficient multi-robot coordination. The paper presents a novel method of multi-robot coordination based on an Artificial Immune System. The developed approach relies on Jern’s Immune Network Theory, which concerns how an antibody stimulates or suppresses another antibody and recognizes non-self antigens. In the present work, the robots are analogous to antibodies and the robotic task is analogous to an antigen in a biological immune system. Furthermore, stimulation and suppression in an immune system correspond to communication among robots. The artificial immune system will select the appropriate number of antibodies autonomously to eliminate the antigens. The developed method of multirobot coordination is verified by computer simulation.Copyright

Object Pose Estimation for Multi-Robot Cooperative Object Transportation

Object recognition and pose estimation are essential for an object transportation system with mobile robots. This paper investigates an approach for pose (position and orientation) estimation of an ordinary object using a laser range finder mounted on the mobile robot. First the CCD camera of the robot finds and identifies an object to be transported in the work environment. On locating a color blob marked on the object, the robot adjusts its pose to move the color blob into the center of the camera frame. Finally a laser range finder is activated to compute the distance and the angle between the laser source and the object. The information acquired in this manner is utilized by the robot to determine a proper pushing location on the object to be transported to goal location. The developed methodology is verified by a series of physical experiments. In the experiments, the object is placed at different positions and orientations and the developed scheme is executed in order to establish its robustness.Copyright

AUCTION-BASED FAULT-TOLERANT MULTI-ROBOT COOPERATION

This paper presents a market driven approach for robust multi-robot cooperation. The example task that is considered is object transportation from an original location to a goal location. The developed methodology relies on market-based decision making, which uses auction as a process of assigning a task to a robot by offering it up for a bid. In the event of robot failure during the execution of a task, the task is re-allocated to another suitable robot using the same auctioning process. This paper addresses two possible robot malfunctions—partial and full failures, which can happen any time during the execution of a task. The practicability of the developed methodology is demonstrated by implementing an auction-based approach on a team of simulated robots that cooperatively execute a task.

Robust Multi-Robot Cooperation Using an Idiotypic Model of Artificial Immune Systems

The human immune system is a network of cells, tissues, and other organs that defend the body against foreign invaders called antigens. Jerne’s Idiotypic network theory concerns how an antibody in the immune system stimulates or suppresses another antibody and recognizes an antigen. Based on the principles of the human immune system and Jerne’s idiotypic network theory this paper presents a method for cooperation among robots in a multi-robot system. The developed cooperative multi-robot system is fully autonomous and distributed. In the present paper, cooperation is not assumed a priori. If a robot is unable to complete a task alone, the system autonomously chooses the appropriate number of suitable and most capable robots in the fleet to cooperate with each other in carrying out a global task. The approach developed in the paper incorporates robustness and fault tolerance in immune system–based multi-robot cooperation.Copyright