Showing papers on "Mobile robot published in 2013"

A Survey and Analysis of Multi-Robot Coordination

Abstract: In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.

A robust and modular multi-sensor fusion approach applied to MAV navigation

Abstract: It has been long known that fusing information from multiple sensors for robot navigation results in increased robustness and accuracy. However, accurate calibration of the sensor ensemble prior to deployment in the field as well as coping with sensor outages, different measurement rates and delays, render multi-sensor fusion a challenge. As a result, most often, systems do not exploit all the sensor information available in exchange for simplicity. For example, on a mission requiring transition of the robot from indoors to outdoors, it is the norm to ignore the Global Positioning System (GPS) signals which become freely available once outdoors and instead, rely only on sensor feeds (e.g., vision and laser) continuously available throughout the mission. Naturally, this comes at the expense of robustness and accuracy in real deployment. This paper presents a generic framework, dubbed MultiSensor-Fusion Extended Kalman Filter (MSF-EKF), able to process delayed, relative and absolute measurements from a theoretically unlimited number of different sensors and sensor types, while allowing self-calibration of the sensor-suite online. The modularity of MSF-EKF allows seamless handling of additional/lost sensor signals during operation while employing a state buffering scheme augmented with Iterated EKF (IEKF) updates to allow for efficient re-linearization of the prediction to get near optimal linearization points for both absolute and relative state updates. We demonstrate our approach in outdoor navigation experiments using a Micro Aerial Vehicle (MAV) equipped with a GPS receiver as well as visual, inertial, and pressure sensors.

Towards dynamic trot gait locomotion: Design, control, and experiments with Cheetah-cub, a compliant quadruped robot

Abstract: We present the design of a novel compliant quadruped robot, called Cheetah-cub, and a series of locomotion experiments with fast trotting gaits. The robot's leg configuration is based on a spring-loaded, pantograph mechanism with multiple segments. A dedicated open-loop locomotion controller was derived and implemented. Experiments were run in simulation and in hardware on flat terrain and with a step down, demonstrating the robot's self-stabilizing properties. The robot reached a running trot with short flight phases with a maximum Froude number of FR = 1.30, or 6.9 body lengths per second. Morphological parameters such as the leg design also played a role. By adding distal in-series elasticity, self-stability and maximum robot speed improved. Our robot has several advantages, especially when compared with larger and stiffer quadruped robot designs. (1) It is, to the best of the authors' knowledge, the fastest of all quadruped robots below 30kg (in terms of Froude number and body lengths per second). (2) It shows self-stabilizing behavior over a large range of speeds with open-loop control. (3) It is lightweight, compact, and electrically powered. (4) It is cheap, easy to reproduce, robust, and safe to handle. This makes it an excellent tool for research of multi-segment legs in quadruped robots.

A review of mobile robotic telepresence

Abstract: Mobile robotic telepresence (MRP) systems incorporate video conferencing equipment onto mobile robot devices which can be steered from remote locations. These systems, which are primarily used in the context of promoting social interaction between people, are becoming increasingly popular within certain application domains such as health care environments, independent living for the elderly, and office environments. In this paper, an overview of the various systems, application areas, and challenges found in the literature concerning mobile robotic telepresence is provided. The survey also proposes a set terminology for the field as there is currently a lack of standard terms for the different concepts related to MRP systems. Further, this paper provides an outlook on the various research directions for developing and enhancing mobile robotic telepresence systems per se, as well as evaluating the interaction in laboratory and field settings. Finally, the survey outlines a number of design implications for the future of mobile robotic telepresence systems for social interaction.

EEG-Based Brain-Controlled Mobile Robots: A Survey

Abstract: EEG-based brain-controlled mobile robots can serve as powerful aids for severely disabled people in their daily life, especially to help them move voluntarily. In this paper, we provide a comprehensive review of the complete systems, key techniques, and evaluation issues of brain-controlled mobile robots along with some insights into related future research and development issues. We first review and classify various complete systems of brain-controlled mobile robots into two categories from the perspective of their operational modes. We then describe key techniques that are used in these brain-controlled mobile robots including the brain-computer interface techniques and shared control techniques. This description is followed by an analysis of the evaluation issues of brain-controlled mobile robots including participants, tasks and environments, and evaluation metrics. We conclude this paper with a discussion of the current challenges and future research directions.

Human-robot collaborative manipulation planning using early prediction of human motion

Abstract: In this paper we present a framework that allows a human and a robot to perform simultaneous manipulation tasks safely in close proximity. The proposed framework is based on early prediction of the human's motion. The prediction system, which builds on previous work in the area of gesture recognition, generates a prediction of human workspace occupancy by computing the swept volume of learned human motion trajectories. The motion planner then plans robot trajectories that minimize a penetration cost in the human workspace occupancy while interleaving planning and execution. Multiple plans are computed in parallel, one for each robot task available at the current time, and the trajectory with the least cost is selected for execution. We test our framework in simulation using recorded human motions and a simulated PR2 robot. Our results show that our framework enables the robot to avoid the human while still accomplishing the robot's task, even in cases where the initial prediction of the human's motion is incorrect. We also show that taking into account the predicted human workspace occupancy in the robot's motion planner leads to safer and more efficient interactions between the user and the robot than only considering the human's current configuration.

Autonomous undulatory serpentine locomotion utilizing body dynamics of a fluidic soft robot

Abstract: Soft robotics offers the unique promise of creating inherently safe and adaptive systems. These systems bring man-made machines closer to the natural capabilities of biological systems. An important requirement to enable self-contained soft mobile robots is an on-board power source. In this paper, we present an approach to create a bio-inspired soft robotic snake that can undulate in a similar way to its biological counterpart using pressure for actuation power, without human intervention. With this approach, we develop an autonomous soft snake robot with on-board actuation, power, computation and control capabilities. The robot consists of four bidirectional fluidic elastomer actuators in series to create a traveling curvature wave from head to tail along its body. Passive wheels between segments generate the necessary frictional anisotropy for forward locomotion. It takes 14 h to build the soft robotic snake, which can attain an average locomotion speed of 19 mm s−1.

An Origami-Inspired Approach to Worm Robots

Abstract: This paper presents an origami-inspired technique which allows the application of 2-D fabrication methods to build 3-D robotic systems. The ability to design robots as origami structures introduces a fast and low-cost fabrication method to modern, real-world robotic applications. We employ laser-machined origami patterns to build a new class of robotic systems for mobility and manipulation. Origami robots use only a flat sheet as the base structure for building complicated bodies. An arbitrarily complex folding pattern can be used to yield an array of functionalities, in the form of actuated hinges or active spring elements. For actuation, we use compact NiTi coil actuators placed on the body to move parts of the structure on-demand. We demonstrate, as a proof-of-concept case study, the end-to-end fabrication and assembly of a simple mobile robot that can undergo worm-like peristaltic locomotion.

An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications

Abstract: Robust velocity and position estimation at high update rates is crucial for mobile robot navigation. In recent years optical flow sensors based on computer mouse hardware chips have been shown to perform well on micro air vehicles. Since they require more light than present in typical indoor and outdoor low-light conditions, their practical use is limited. We present an open source and open hardware design 1 of an optical flow sensor based on a machine vision CMOS image sensor for indoor and outdoor applications with very high light sensitivity. Optical flow is estimated on an ARM Cortex M4 microcontroller in real-time at 250 Hz update rate. Angular rate compensation with a gyroscope and distance scaling using a ultrasonic sensor are performed onboard. The system is designed for further extension and adaption and shown in-flight on a micro air vehicle.

Control of an aerial robot with multi-link arm for assembly tasks

Abstract: This paper deals with aerial manipulators consisting of an unmanned aerial vehicle equipped with a robotic multi-link arm. The paper presents methods for the control of the aerial platform taking into account the motion of the arm. It shows how a Variable Parameter Integral Backstepping controller outperforms the results obtained by using PID controllers. The paper presents a quadrotor with a new arm designed for assembly tasks and the implementation of the proposed control methods. Simulations and outdoor experiments confirm the validity of the proposed approach.

Tour Planning for Mobile Data-Gathering Mechanisms in Wireless Sensor Networks

Abstract: In this paper, we propose a new data-gathering mechanism for large-scale wireless sensor networks by introducing mobility into the network. A mobile data collector, for convenience called an M-collector in this paper, could be a mobile robot or a vehicle equipped with a powerful transceiver and battery, working like a mobile base station and gathering data while moving through the field. An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Since data packets are directly gathered without relays and collisions, the lifetime of sensors is expected to be prolonged. In this paper, we mainly focus on the problem of minimizing the length of each data-gathering tour and refer to this as the single-hop data-gathering problem (SHDGP). We first formalize the SHDGP into a mixed-integer program and then present a heuristic tour-planning algorithm for the case where a single M-collector is employed. For the applications with strict distance/time constraints, we consider utilizing multiple M-collectors and propose a data-gathering algorithm where multiple M-collectors traverse through several shorter subtours concurrently to satisfy the distance/time constraints. Our single-hop mobile data-gathering scheme can improve the scalability and balance the energy consumption among sensors. It can be used in both connected and disconnected networks. Simulation results demonstrate that the proposed data-gathering algorithm can greatly shorten the moving distance of the collectors compared with the covering line approximation algorithm and is close to the optimal algorithm for small networks. In addition, the proposed data-gathering scheme can significantly prolong the network lifetime compared with a network with static data sink or a network in which the mobile collector can only move along straight lines.

Dynamic Whole-Body Motion Generation Under Rigid Contacts and Other Unilateral Constraints

Abstract: The most widely used technique for generating whole-body motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost. To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot.

M-blocks: Momentum-driven, magnetic modular robots

Abstract: In this paper, we describe a novel self-assembling, self-reconfiguring cubic robot that uses pivoting motions to change its intended geometry. Each individual module can pivot to move linearly on a substrate of stationary modules. The modules can use the same operation to perform convex and concave transitions to change planes. Each module can also move independently to traverse planar unstructured environments. The modules achieve these movements by quickly transferring angular momentum accumulated in a self-contained flywheel to the body of the robot. The system provides a simplified realization of the modular actions required by the sliding cube model using pivoting. We describe the principles, the unit-module hardware, and extensive experiments with a system of eight modules.

Robust loop closing over time for pose graph SLAM

Abstract: Long-term autonomous mobile robot operation requires considering place recognition decisions with great caution. A single incorrect decision that is not detected and reconsidered can corrupt the environment model that the robot is trying to build and maintain. This work describes a consensus-based approach to robust place recognition over time, that takes into account all the available information to detect and remove past incorrect loop closures. The main novelties of our work are: (1) the ability of realizing that, in light of new evidence, an incorrect past loop closing decision has been made; the incorrect information can be removed thus recovering the correct estimation with a novel algorithm; (2) extending our proposal to incremental operation; and (3) handling multi-session, spatially related or unrelated scenarios in a unified manner. We demonstrate our proposal, the RRR algorithm, on different odometry systems, e.g. visual or laser, using different front-end loop-closing techniques. For our experiments we use the efficient graph optimization framework g2o as back-end. We back our claims up with several experiments carried out on real data, in single and multi-session experiments showing better results than those obtained by state-of-the-art methods, comparisons against whom are also presented.

Robot companion: A social-force based approach with human awareness-navigation in crowded environments

Abstract: Robots accompanying humans is one of the core capacities every service robot deployed in urban settings should have. We present a novel robot companion approach based on the so-called Social Force Model (SFM). A new model of robot-person interaction is obtained using the SFM which is suited for our robots Tibi and Dabo. Additionally, we propose an interactive scheme for robot's human-awareness navigation using the SFM and prediction information. Moreover, we present a new metric to evaluate the robot companion performance based on vital spaces and comfortableness criteria. Also, a multimodal human feedback is proposed to enhance the behavior of the system. The validation of the model is accomplished throughout an extensive set of simulations and real-life experiments.

A Deterministic Improved Q-Learning for Path Planning of a Mobile Robot

Abstract: This paper provides a new deterministic Q-learning with a presumed knowledge about the distance from the current state to both the next state and the goal. This knowledge is efficiently used to update the entries in the Q-table once only by utilizing four derived properties of the Q-learning, instead of repeatedly updating them like the classical Q-learning. Naturally, the proposed algorithm has an insignificantly small time complexity in comparison to its classical counterpart. Furthermore, the proposed algorithm stores the Q-value for the best possible action at a state and thus saves significant storage. Experiments undertaken on simulated maze and real platforms confirm that the Q-table obtained by the proposed Q-learning when used for the path-planning application of mobile robots outperforms both the classical and the extended Q-learning with respect to three metrics: traversal time, number of states traversed, and 90° turns required. The reduction in 90° turnings minimizes the energy consumption and thus has importance in the robotics literature.

Safety issues in human-robot interactions

Abstract: Safety is an important consideration in human-robot interactions (HRI). Robots can perform powerful movements that can cause hazards to humans surrounding them. To prevent accidents, it is important to identify sources of potential harm, to determine which of the persons in the robot's vicinity may be in greatest peril and to assess the type of injuries the robot may cause to this person. This survey starts with a review of the safety issues in industrial settings, where robots manipulate dangerous tools and move with extreme rapidity and force. We then move to covering issues related to the growing numbers of autonomous mobile robots that operate in crowded (human-inhabited) environments. We discuss the potential benefits of fully autonomous cars on safety on roads and for pedestrians. Lastly, we cover safety issues related to assistive robots.

Contextually guided semantic labeling and search for three-dimensional point clouds

Abstract: RGB-D cameras, which give an RGB image together with depths, are becoming increasingly popular for robotic perception. In this paper, we address the task of detecting commonly found objects in the three-dimensional (3D) point cloud of indoor scenes obtained from such cameras. Our method uses a graphical model that captures various features and contextual relations, including the local visual appearance and shape cues, object co-occurrence relationships and geometric relationships. With a large number of object classes and relations, the model's parsimony becomes important and we address that by using multiple types of edge potentials. We train the model using a maximum-margin learning approach. In our experiments concerning a total of 52 3D scenes of homes and offices (composed from about 550 views), we get a performance of 84.06% and 73.38% in labeling office and home scenes respectively for 17 object classes each. We also present a method for a robot to search for an object using the learned model and the contextual information available from the current labelings of the scene. We applied this algorithm successfully on a mobile robot for the task of finding 12 object classes in 10 different offices and achieved a precision of 97.56% with 78.43% recall.1

IkeaBot: An autonomous multi-robot coordinated furniture assembly system

Abstract: We present an automated assembly system that directs the actions of a team of heterogeneous robots in the completion of an assembly task. From an initial user-supplied geometric specification, the system applies reasoning about the geometry of individual parts in order to deduce how they fit together. The task is then automatically transformed to a symbolic description of the assembly-a sort of blueprint. A symbolic planner generates an assembly sequence that can be executed by a team of collaborating robots. Each robot fulfills one of two roles: parts delivery or parts assembly. The latter are equipped with specialized tools to aid in the assembly process. Additionally, the robots engage in coordinated co-manipulation of large, heavy assemblies. We provide details of an example furniture kit assembled by the system.

Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms

Abstract: Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion, the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposes an integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-based plume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitive micro-drone. We compare the performance of the proposed system in simulations and real-world experiments against two commonly used tracking algorithms adapted for aerial exploration missions.

Distributed Cohesive Motion Control of Flight Vehicle Formations

Abstract: In this paper, we consider the problem of decentralized cohesive motion control of a formation of autonomous vehicles or robots moving in three dimensions, where the formation is required to move from its initial setting (defined by the positions of the agents in the formation) to a final desired setting and, during this motion, maintain its formation geometry defined by the initial distances between the agent pairs We propose a distributed control scheme to solve this problem utilizing the notions of graph rigidity and persistence as well as techniques of virtual target tracking and smooth switching The distributed control scheme is developed by modeling the agent kinematics as single-velocity integrator; nevertheless, extension to the cases with practical kinematic and dynamic models of fixed-wing autonomous aerial vehicles and quadrotors is discussed In this context, we examine the maintenance of geometric formation of a swarm of autonomous flight vehicles The developed coordination and control schemes are verified via a number of simulations

Robot navigation in dense human crowds: the case for cooperation

Abstract: We consider mobile robot navigation in dense human crowds. In particular, we explore two questions. Can we design a navigation algorithm that encourages humans to cooperate with a robot? Would such cooperation improve navigation performance? We address the first question by developing a probabilistic predictive model of cooperative collision avoidance and goal-oriented behavior by extending the interacting Gaussian processes approach to include multiple goals and stochastic movement duration. We answer the second question with an extensive quantitative study of robot navigation in dense human crowds (488 runs completed), specifically testing how cooperation models effect navigation performance. We find that the “multiple goal” interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities near 1 person/m2, while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as this multiple goal extension, and more than twice as often as the basic interacting Gaussian processes. Furthermore, a reactive planner based on the widely used “dynamic window” approach fails for crowd densities above 0.55 people/m2. Based on these experimental results, and previous theoretical observations, we conclude that a cooperation model is important for safe and efficient robot navigation in dense human crowds.

Environmental management systems including mobile robots and methods using same

Abstract: A computer-implemented method for receiving user commands for a remote cleaning robot and sending the user commands to the remote cleaning robot, the remote cleaning robot including a drive motor and a cleaning motor, includes displaying a user interface including a control area, and within the control area: a user-manipulable launch control group including a plurality of control elements, the launch control group having a deferred launch control state and an immediate launch control state; at least one user-manipulable cleaning strategy control element having a primary cleaning strategy control state and an alternative cleaning strategy control state; and a physical recall control group including a plurality of control elements, the physical recall control group having an immediate recall control state and a remote audible locator control state. The method further includes: receiving user input via the user-manipulable control elements; responsive to the user inputs, displaying simultaneously within the same control area a real-time robot state reflecting a unique combination of control states; and commanding the remote cleaning robot to actuate the drive motor and cleaning motor to clean a surface based on the received input and unique combination of control states.

Dynamic Modelling of Differential-Drive Mobile Robots using Lagrange and Newton-Euler Methodologies: A Unified Framework

Abstract: This paper presents a unified dynamic modeling framework for differential-drive mobile robots (DDMR). Two formulations for mobile robot dynamics are developed; one is based on Lagrangian mechanics, and the other on Newton-Euler mechanics. Major difficulties experienced when modeling non-holonomic systems in both methods are illustrated and design procedures are outlined. It is shown that the two formulations are mathematically equivalent providing a check on their consistency. The presented work leads to an improved understanding of differentialdrive mobile robot dynamics, which will assist engineering students and researchers in the modeling and design of suitable controllers for DDMR navigation and trajectory tracking.

Human-robot physical interaction and collaboration using an industrial robot with a closed control architecture

Abstract: In physical Human-Robot Interaction, the basic problem of fast detection and safe robot reaction to unexpected collisions has been addressed successfully on advanced research robots that are torque controlled, possibly equipped with joint torque sensors, and for which an accurate dynamic model is available. In this paper, an end-user approach to collision detection and reaction is presented for an industrial manipulator having a closed control architecture and no additional sensors. The proposed detection and reaction schemes have minimal requirements: only the outer joint velocity reference to the robot manufacturer's controller is used, together with the available measurements of motor currents and joint positions. No a priori information on the robot dynamic model and existing low-level joint controllers is strictly needed. A suitable on-line processing of the motor currents allows to distinguish between accidental collisions and intended human-robot contacts, so as to switch the robot to a collaboration mode when needed. Two examples of reaction schemes for collaboration are presented, with the user pushing/pulling the robot at any point of its structure (e.g., for manual guidance) or with a compliant-like robot behavior in response to forces applied by the human. The actual performance of the methods is illustrated through experiments on a KUKA KR5 manipulator.

Robot self-assembly by folding: A printed inchworm robot

Abstract: Printing and folding are fast and inexpensive methods for prototyping complex machines. Self-assembly of the folding step would expand the possibilities of this method to include applications where external manipulation is costly, such as micro-assembly, mass production, and space applications. This paper presents a method for self-folding of printed robots from two-dimensional materials based on shape memory polymers actuated by joule heating using embedded circuits. This method was shown to be capable of sequential folding, angle-controlled folds, slot-and-tab assembly, and mountain and valley folds. An inchworm robot was designed to demonstrate the merits of this technique. Upon the application of sufficient current, the robot was able to fold into its functional form with fold angle deviations within six degrees. This printed robot demonstrated locomotion at a speed of two millimeters per second.

Efficient trajectory optimization using a sparse model

Abstract: The “timed elastic band” approach optimizes robot trajectories by subsequent modification of an initial trajectory generated by a global planner. The objectives considered in the trajectory optimization include but are not limited to the overall path length, trajectory execution time, separation from obstacles, passing through intermediate way points and compliance with the robots dynamic, kinematic and geometric constraints. “Timed elastic bands” explicitly consider spatial-temporal aspects of the motion in terms of dynamic constraints such as limited robot velocities and accelerations. The trajectory planning operates in real time such that “timed elastic bands” cope with dynamic obstacles and motion constraints. The “timed elastic band problem” is formulated as a scalarized multi-objective optimization problem. Most objectives are local and relate to only a small subset of parameters as they only depend on a few consecutive robot states. This local structure results in a sparse system matrix, which allows the utilization of fast and efficient optimization techniques such as the open-source framework “g2o” for solving “timed elastic band” problems. The “g2o” sparse system solvers have been successfully applied to VSLAM problems. This contribution describes the application and adaptation of the g2o-framework in the context of trajectory modification with the “timed elastic band”. Results from simulations and experiments with a real robot demonstrate that the implementation is robust and computationally efficient.