Robotics and Autonomous Systems Social potential fields

2009 IEEE International Conference on Robotics and Automation, 2009

We present a novel approach to compute collisionfree paths for multiple robots subject to local coordination constraints. More specifically, given a set of robots, their initial and final configurations, and possibly some additional coordination constraints, our goal is to compute a collision-free path between the initial and final configuration that maintains the constraints. To solve this problem, our approach generalizes the social potential field method to be applicable to both convex and nonconvex polyhedra. Social potential fields are then integrated into a "physics-based motion planning" framework which uses constrained dynamics to solve the motion planning problem. Our approach is able to plan for over 200 robots while averaging about 110 ms per step in a variety of environments.

Journal of Dynamic Systems, Measurement, and Control, 2018

We present a novel approach to achieve decentralized distribution of forces in a multirobot system. In this approach, each robot in the group relies on the behavior of a cooperative virtual teammate that is defined independent of the population and formation of the real team. Consequently, such formulation eliminates the need for interagent communications or leader–follower architectures. In particular, effectiveness of the method is studied in a collective manipulation problem where the objective is to control the position and orientation of a body in time. To experimentally validate the performance of the proposed method, a new swarm agent, Δρ (Delta-Rho), is introduced. A multirobot system, consisting of five Δρ agents, is then utilized as the experimental setup. The obtained results are also compared with a norm-optimal centralized controller by quantitative metrics. Experimental results prove the performance of the algorithm in different tested scenarios and demonstrate a scala...

We introduce a new method of artificial potential forces based on probabilistic communication, called 'Probabilistic Communication based Potential Forces'-PCPF. The potential forces provides a locally distributed control for a formation of a large volume of self-regulated mobile robots. While models of sensing and communication so fare mostly have been with simple assumptions that are far away from the physical properties of sensors and communication mechanisms, the method here is realistic because both attractive and repulsive forces are only based on probability of communication which are empirically measured and approximately estimated between robots. The method is demonstrated through non-trivial examples of robot formation and formation transformation. Analysis is provided to facilitate understanding of the elements of the probabilistic method.

Human Behavior Understanding in Networked Sensing, 2014

Institutional robotics (IR) is an approach to the coordination of multirobot systems that draws inspiration from social sciences, namely from institutional economics. Using the concept of institution, it aims to provide a comprehensive strategy for specifying social interactions (e.g., norms, roles, hierarchies) among robots. In previous work, we have introduced a control methodology for multirobot systems that takes into account institutions in order to create an Institutional Agent Controller (IAC) that captures such social interactions. In this chapter, the IAC design methodology is validated in a case study concerned with a swarm of 40 real, resource-constrained robots which has to maintain wireless connectivity. We then investigate a second case study dealing with more complex social interactions, showing that institutional roles can effectively help a multi-robot system to coordinate and improve performance in a given task of social nature. Given the fact that institutions are one of the tools in use within human societies to shape social interactions, our intuition is that IR can also facilitate coordination with humans in scenarios involving many-to-many human-robot interactions. We discuss how the IR concepts and the IAC design methodology can be implemented in real-world scenarios where multiple robots must interact with multiple humans in a socially-aware manner.

Springer Tracts in Advanced Robotics, 2005

This paper addresses the design of simple robot behaviors that realize emergent group behaviors. We present a method to coordinate a large number of under-actuated robots by designing control laws on a small dimensional abstraction manifold, independent of the number and ordering of the robots. The abstraction manifold has a product structure consisting of elements of a Lie group that capture the position and orientation of the ensemble in the world frame, and elements of a shape manifold that provide an intrinsic description of the distribution of team members relative to one another. We design decoupled controls for regulating the group and the shape variables. The realization of the controller on each robot requires the feedback of the robot state, and the state on the abstraction manifold. We present experimental results with a team of five car-like robots equipped with omnidirectional cameras and IEEE 802.11b networking.

Robotics and Autonomous Systems, 2009

Previously our novel Shared Potential Field (SPF) method has been introduced and compared against a non-sharing control in both simulation and laboratory settings. In this paper, extended from a paper presented at the CIRAS 2008 conference, we compare the SPF against an existing type of robot architecture, a hybrid robotic system. The SPF method is compared to the traditional potential field method, and it is shown that the SPF is less susceptible to the traditional limitations of potential fields. The SPF method's position in Farinelli's multi-robot taxonomy is also discussed, and it is shown that rather than being placed in one category it encompasses two, corresponding to the two levels of control within the architecture. In experiments, the multi-robot systems are given the task of traversing an unknown environment, in an attempt to locate a target. The metric of performance for this task was the time taken to find the target. Experiments show that the hybrid system showed similar performance to the non-sharing control. In contrast, our Pessimistic variant of the SPF outperformed the hybrid system in the cluttered environment, and the Optimistic SPF variant outperformed the hybrid system in the sparse environment. We conclude that the SPF method reacts more robustly to the dynamic nature of the real world, and so performed significantly better throughout the experimentation.

Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05, 2005

In this paper we present a distributed control scheme for a group of cooperating roving robots. It is based on the model introduced by Vicsek [1], which models the kinetics of self-propelled particles, able to undergo a phase transition from a disordered state to an ordered state, involving a net transport phenomenon. We examine the case in which the noise term is not zero and provide a simple explanation for this case. Moreover, the properties of small-world topology are considered in order to include long-range connections between the robots. This leads to an improvement of system performance in presence of noise. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

Lecture Notes in Computer Science, 2009

This paper focuses on the implementation and evaluation of a set of integrated models for the representation of emergent behavior control patterns in robotic environments. The models have been validated on a custom developed emergent behavior simulator and tested using the CORE-TX (COllaborative Robotic Environment -the Timisoara eXperiment) prototype platform. Four metrics (pheromone intensity, path affinity, reachability and liveness) are introduced and used to evaluate the performance of the proposed control patterns. Experimental results for an environment which employs ant colony behavior patterns in obstacle avoidance applications show that the emergent behavior of the robotic collective is triggered by a number ranging from 9 to 11 entities. The results are also consistent with the theoretical model-based predictions. When doubling the number of entities, the performance of the system can be further increased by 19.3%. On the other hand, a high concentration of entities has been noted to affect the emergent behavior of the system and, thus, its performance, mainly due to the interaction overhead. An upper bound to the number of individuals has been computed, based on a set of parameters which model each particular application. The experimental validation of the proposed behavior control patterns endorses them as a good framework for the analysis and development of complex applications which require collaborative and distributed intelligence, perception and operation.

IFAC-PapersOnLine

This paper deals with the path planning problem of a group of autonomous Wheeled Mobile Robots in a very dynamic workspace. The idea consists of considering the system of group of robots as a robot network with decentralized architecture. Each robot plans its trajectory according to its actual position, the position of the other neighbor robots, the position of the obstacles and the position of its target point. So each robot should interact with the other robots in the network to cooperate together in order to plan each robot trajectory. The path planning for every robot is planned based on the potential field approach. The network reacts with the changes of workspace in real time by updating the system equations associated for each robot. The main objective of this work is to avoid collision between robots and obstacles in order to ensure the safety of robots. The solution is tested and simulated with Matlab/Simulink and Solidworks/Simmechanics.

22nd Digital Avionics Systems Conference Proceedings (Cat No 03CH37449) DASC-03, 2003