in this paper, according to high load capacity and rather large workspace characteristics of cable driven robots (cdrs), maximum dynamic load carrying capacity (dlcc) between two given end points in the workspace along with optimal trajectory is obtained. in order to find dlcc of cdrs, joint actuator torque and workspace of the robot constraints concerning to non-negative tension in cables are ...

cooperative object manipulation control of rigid-flexible multi-body systems in space is studied in this paper. during such tasks, flexible members like solar panels may get vibrated that in turn may lead to some oscillatory disturbing forces on other subsystems, and consequently produces error in the motion of the end-effectors of the cooperative manipulating arms. therefore, to design and dev...

trajectories generally used to describe the space and time required to perform a desired motion task for a mobile robot or manipulator system. in this paper, we considered a cubic polynomial trajectory for the problem of moving a mobile robot from its initial position to a goal position in over a continuous set of time. along the path, the robot requires to observe a certain acceleration profil...

Designing and controlling simple collective robot behaviors often requires complex range and bearing sensors and peerto-peer communication strategies. Recent work studying swarms robots that have no computational power has shown that complex behaviors such as aggregation and clustering items can be produced from extremely simple control policies and sensing capability. We extend previous work o...

We review existing approaches to mathematical modeling and analysis of multi-agent systems in which complex collective behavior arises out of local interactions between many simple agents. Though the behavior of an individual agent can be considered to be stochastic and unpredictable, the collective behavior of such systems can have a simple probabilistic description. We show that a class of ma...

The learning and reasoning capabilities of biological systems by far exceed those of robots and artificial agents. Part of this stems from their ability to efficiently learn behavioral skills and increasingly complex, symbolic representations that capture the important aspects of their environment. This paper presents an autonomous learning approach by which artificial reinforcement learning ag...

In many cases cooperation between robots is implemented using explicit perhaps complex coordination protocols However research in behavior based multirobot systems suggests that e ective cooperative teams can be composed of agents using simple individual agent behaviors with limited or no communication In this paper we propose behavioral diversity as an alternative cooperative strategy Behavior...

Swarm intelligence (SI) is based on collective behavior of selforganized systems. Typical swarm intelligence schemes include Particle Swarm Optimization (PSO), Ant Colony System (ACS), Stochastic Diffusion Search (SDS), Bacteria Foraging (BF), the Artificial Bee Colony (ABC), and so on. Besides the applications to conventional optimization problems, SI can be used in controlling robots and unma...

The general framework tackled in this paper is the automatic generation of intelligent collective behaviors using genetic programming and reinforcement learning. We define a behavior-based system relying on automatic design process using artificial evolution to synthesize high level behaviors for autonomous agents. Behavioral strategies are described by tree-based structures, and manipulated by...

In this paper, we review methods used for macroscopic modeling and analyzing collective behavior of swarm robotic systems. Although the behavior of an individual robot in a swarm is often characterized by an important stochastic component, the collective behavior of swarms is statistically predictable and has often a simple probabilistic description. Indeed, we show that a class of mathematical...