This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

Cooperative mobile robotics: antecedents and directions

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, the authors give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. The authors describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

/pdf/cooperative-mobile-robotics-antecedents-and-directions-18nltan2ev.pdf

A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent systems, with the dual purposes of illustrating the usefulness of the taxonomy in simplifying discourse about robot collective properties, and also demonstrating that a collective can be demonstrably more powerful than a single unit of the collective.

A Taxonomy for Multi-Agent Robotics*

There has been increasing interest in a type of underactuated mechanical systems, mobile-wheeled inverted-pendulum (MWIP) models, which are widely used in the field of autonomous robotics and intelligent vehicles. Robust-velocity-tracking problem of the MWIP systems is investigated in this study. In the velocity-control problem, model uncertainties accompany uncertain equilibriums, which make the controller design become more difficult. Two sliding-mode-control (SMC) methods are proposed for the systems, both of which are capable of handling both parameter uncertainties and external disturbances. The asymptotical stabilities of the corresponding closed-loop systems are achieved through the selection of sliding-surface parameters, which are based on some rules. There is still a steady tracking error when the first SMC controller is used. By assuming a novel sliding surface, the second SMC controller is designed to solve this problem. The effectiveness of the proposed methods is finally confirmed by the numerical simulations.

Sliding-Mode Velocity Control of Mobile-Wheeled Inverted-Pendulum Systems

This paper proposes a 3-D biped dynamic walking algorithm based on passive dynamic autonomous control (PDAC). The robot dynamics is modeled as an autonomous system of a 3-D inverted pendulum by applying the PDAC concept that is based on the assumption of point contact of the robot foot and the virtual constraint as to robot joints. Due to autonomy, there are two conservative quantities named ldquoPDAC constant,rdquo which determine the velocity and direction of the biped walking. We also propose the convergence algorithm to make PDAC constants converge to arbitrary values, so that walking velocity and direction are controllable. Finally, experimental results validate the performance and the energy efficiency of the proposed algorithm.

/pdf/stabilizing-and-direction-control-of-efficient-3-d-biped-5asa6aeed9.pdf

Stabilizing and Direction Control of Efficient 3-D Biped Walking Based on PDAC

This paper introduces a vertical ladder climbing of the humanoid robot only by the posture control without any external sensors. The humanoid robot does not have any special structure for fixing the body to the ladder. The robot maintains the body on the ladder by its grippers like human does. As a problem of this locomotion, a free gripper position of the climbing robot is not controllable because a yawing of the robot body around the axis connecting a supporting gripper and foot on the ladder is not fixed. To solve this problem, the momentum around AOY caused by the gravity is used to control the yaw motion of the body so that the various gait such as pace gait and trot gait could be realized in a ladder climbing maneuver. The algorithm of ladder climbing with recovery motion is experimentally verified by using ldquomulti-locomotion robot(MLR)rdquo which is developed to achieve various types of locomotion such as biped, quadruped walking and brachiation.

/pdf/vertical-ladder-climbing-motion-with-posture-control-for-243s3rmv77.pdf

Vertical ladder climbing motion with posture control for multi-locomotion robot

A three-wheeled omni-directional cane robot is designed for aiding the elderly walking A new human fall detection method is proposed based on fusing sensory information from a vision system and a laser ranger finder (LRF) This method plays an important role in the fall-prevention for the cane robot The human fall model is represented in a 2D space, where the distance between the head and the average leg position is a significant feature to detect the fall The possibility distribution of this distance is estimated by using Dubois possibility theory Fall detection is implemented by using a simple rule based on the possibility distribution The proposed method is confirmed through experiments

Study of Fall Detection Using Intelligent Cane Based on Sensor Fusion

Research topics in robotic application is quite varies but one of the most interesting topic is odor source localization. This research combine the robot ability to recognize odor and track the movement so that robot can find the source. Most of the research are done to improve the algorithm to localize the source by using simulation software. This paper tries to verify the robustness of one of the localization method known as Particle Swarm Optimization (PSO) in the real-world implementation. This paper will shows robot model that used in the experiment and also discuss the architecture to implement robot behavior. A group of mobile robots equipped with wireless communication device and odor sensors is employed. The experiment is conduct in area of 488cm × 488cm with dynamic odor source in one end. The experiment also used a set of camera to track robots position. The experiement result verifies that PSO is technically sound for real-world odor source localization. In this experiment, PSO can localized the source in 360 seconds or bellow.

Robots implementation for odor source localization using PSO algorithm

This paper deals with a unified system of fully distributed meshed sensor network and mobile robot cooperation that serves as a sink node. The meshed sensor network in this paper is composed of static wireless nodes, and is capable of fully distributed peer-to-peer (P2P) ad hoc communication with ZigBee-based protocol. A novel communication timing control employing coupled-oscillator dynamics, named phase-diffusion time-division method (PDTD), has been proposed so far, aiming at realization of an ad hoc collision-free wireless communication network. In this paper, we extend the basic PDTD so that it can exhibit flexible topological reconfiguration according to the moving sink node (robot). Unlike conventional sensor network, no static sink node is supposed inside the network; however, a mobile robot will function as a sink node and access the mesh network from an arbitrary position. A large-scale experiment was conducted, and its results show that satisfactory collaboration between the mesh sensor network and the mobile robot is achieved, and the proposed system outperformed the carrier-sense-multiple-access-based sensor system.

K. Sekiyama

Papers

Stabilizing and Direction Control of Efficient 3-D Biped Walking Based on PDAC

Vertical ladder climbing motion with posture control for multi-locomotion robot

Study of Fall Detection Using Intelligent Cane Based on Sensor Fusion

Robots implementation for odor source localization using PSO algorithm

Communication Timing Control and Topology Reconfiguration of a Sink-Free Meshed Sensor Network With Mobile Robots