Category Archives: Robotics

A nice SLAM approach based on hybrid Normal Distribution Transform (NDT) + occupancy grid maps intended for long term operation in dynamic environments

May 4, 2015 10:23 ,

Erik Einhorn, Horst-Michael Gross, Generic NDT mapping in dynamic environments and its application for lifelong SLAM, Robotics and Autonomous Systems, Volume 69, July 2015, Pages 28-39, ISSN 0921-8890, DOI: 10.1016/j.robot.2014.08.008.

In this paper, we present a new, generic approach for Simultaneous Localization and Mapping (SLAM). First of all, we propose an abstraction of the underlying sensor data using Normal Distribution Transform (NDT) maps that are suitable for making our approach independent from the used sensor and the dimension of the generated maps. We present several modifications for the original NDT mapping to handle free-space measurements explicitly. We additionally describe a method to detect and handle dynamic objects such as moving persons. This enables the usage of the proposed approach in highly dynamic environments. In the second part of this paper we describe our graph-based SLAM approach that is designed for lifelong usage. Therefore, the memory and computational complexity is limited by pruning the pose graph in an appropriate way.

Posted in: Mobile robot SLAM , Tagged: , , ,

Interesting paper on fault tolerance applied to robotics, with good survey of the subject

April 24, 2015 12:56 ,

D. Crestani, K. Godary-Dejean, L. Lapierre, Enhancing fault tolerance of autonomous mobile robots, Robotics and Autonomous Systems, Volume 68, June 2015, Pages 140-155, ISSN 0921-8890, DOI: 10.1016/j.robot.2014.12.015.

Experience demonstrates that autonomous mobile robots running in the field in a dynamic environment often breakdown. Generally, mobile robots are not designed to efficiently manage faulty or unforeseen situations. Even if some research studies exist, there is a lack of a global approach that really integrates dependability and particularly fault tolerance into the mobile robot design.
This paper presents an approach that aims to integrate fault tolerance principles into the design of a robot real-time control architecture. A failure mode analysis is firstly conducted to identify and characterize the most relevant faults. Then the fault detection and diagnosis mechanisms are explained. Fault detection is based on dedicated software components scanning faulty behaviors. Diagnosis is based on the residual principle and signature analysis to identify faulty software or hardware components and faulty behaviors. Finally, the recovery mechanism, based on the modality principle, proposes to adapt the robot’s control loop according to the context and current operational functions of the robot.
This approach has been applied and implemented in the control architecture of a Pioneer 3DX mobile robot.

Posted in: Robotic software , Tagged:

Novelty detection as a way for enhancing learning capabilities of a robot, and a brief but interesting survey of motivational theories and their difference with attention

April 24, 2015 12:46 ,

Y. Gatsoulis, T.M. McGinnity, Intrinsically motivated learning systems based on biologically-inspired novelty detection, Robotics and Autonomous Systems, Volume 68, June 2015, Pages 12-20, ISSN 0921-8890, DOI: 10.1016/j.robot.2015.02.006.

Intrinsic motivations play an important role in human learning, particularly in the early stages of childhood development, and ideas from this research field have influenced robotic learning and adaptability. In this paper we investigate one specific type of intrinsic motivation, that of novelty detection and we discuss the reasons that make it a powerful facility for continuous learning. We formulate and present one original type of biologically inspired novelty detection architecture and implement it on a robotic system engaged in a perceptual classification task. The results of real-world robot experiments we conducted show how this original architecture conforms to behavioural observations and demonstrate its effectiveness in terms of focusing the system’s attention in areas that are potential for effective learning.

Posted in: Psycho-physiological bases of engineering, Robotics , Tagged: , ,

On the history of IEEE Transactions on Robotics and Automation, ICRA, and others

April 24, 2015 12:23 ,

Sabanovic, S.; Milojevic, S.; Asaro, P.; Francisco, M., Robotics Narratives and Networks [History], Robotics & Automation Magazine, IEEE , vol.22, no.1, pp.137,146, March 2015, DOI: 10.1109/MRA.2014.2385564.

Somewhere around 1983, maybe late 1982, there was talk beginning about doing something more formal within IEEE that dealt with robotics and automation. Informally, activity was getting started through the Control Society,…also Systems, Man and Cybernetics, which obviously makes a lot of sense with the telerobotics things and a few others. But we wanted to build a more permanent home for it, so there was one of the first meetings. George Saridis chaired the meeting. I know George Bekey was there, Tony Bejczy, Lou Paul, probably another half dozen people.

Posted in: History of robotics

Abstract data-type for exchanging information in real-time systems, prioritizing the access to newest data rather than to oldest

April 24, 2015 12:19 ,

Dantam, N.T.; Lofaro, D.M.; Hereid, A.; Oh, P.Y.; Ames, A.D.; Stilman, M., The Ach Library: A New Framework for Real-Time Communication, Robotics & Automation Magazine, IEEE , vol.22, no.1, pp.76,85, March 2015, DOI: 10.1109/MRA.2014.2356937.

Correct real-time software is vital for robots in safety-critical roles such as service and disaster response. These systems depend on software for locomotion, navigation, manipulation, and even seemingly innocuous tasks such as safely regulating battery voltage. A multiprocess software design increases robustness by isolating errors to a single process, allowing the rest of the system to continue operation. This approach also assists with modularity and concurrency. For real-time tasks, such as dynamic balance and force control of manipulators, it is critical to communicate the latest data sample with minimum latency. There are many communication approaches intended for both general-purpose and real-time needs [9], [13], [15], [17], [19]. Typical methods focus on reliable communication or network transparency and accept a tradeoff of increased message latency or the potential to discard newer data. By focusing instead on the specific case of real-time communication on a single host, we reduce communication latency and guarantee access to the latest sample. We present a new interprocess communication (IPC) library, Ach which addresses this need, and discuss its application for real-time multiprocess control on three humanoid robots (Figure 1). (Ach is available at http://www.golems.org/projects/ach.html. The name Ach comes from the common abbreviation for the motor neurotransmitter Acetylcholine and the computer networking term ACK.).

Posted in: Real-Time Systems, Robotic software , Tagged: ,

Reinforcement learning used for an adaptive attention mechanism, and integrated in an architecture with both top-down and bottom-up vision processing

April 24, 2015 11:26 ,

Ognibene, D.; Baldassare, G., Ecological Active Vision: Four Bioinspired Principles to Integrate Bottom–Up and Adaptive Top–Down Attention Tested With a Simple Camera-Arm Robot, Autonomous Mental Development, IEEE Transactions on , vol.7, no.1, pp.3,25, March 2015. DOI: 10.1109/TAMD.2014.2341351.

Vision gives primates a wealth of information useful to manipulate the environment, but at the same time it can easily overwhelm their computational resources. Active vision is a key solution found by nature to solve this problem: a limited fovea actively displaced in space to collect only relevant information. Here we highlight that in ecological conditions this solution encounters four problems: 1) the agent needs to learn where to look based on its goals; 2) manipulation causes learning feedback in areas of space possibly outside the attention focus; 3) good visual actions are needed to guide manipulation actions, but only these can generate learning feedback; and 4) a limited fovea causes aliasing problems. We then propose a computational architecture (“BITPIC”) to overcome the four problems, integrating four bioinspired key ingredients: 1) reinforcement-learning fovea-based top-down attention; 2) a strong vision-manipulation coupling; 3) bottom-up periphery-based attention; and 4) a novel action-oriented memory. The system is tested with a simple simulated camera-arm robot solving a class of search-and-reach tasks involving color-blob “objects.” The results show that the architecture solves the problems, and hence the tasks, very efficiently, and highlight how the architecture principles can contribute to a full exploitation of the advantages of active vision in ecological conditions.

Posted in: Applications of reinforcement learning to robots, Computer vision, Psycho-physiological bases of engineering , Tagged: , , , ,

Automatic synthetis of controllers for robotic tasks from the specification of state-machine-like missions, nonlinear models of the robot and a representation of the robot workspace

March 11, 2015 11:52 ,

Jonathan A. DeCastro and Hadas Kress-Gazit, 2015, Synthesis of nonlinear continuous controllers for verifiably correct high-level, reactive behaviors, The International Journal of Robotics Research, 34: 378-394, DOI: 10.1177/0278364914557736.

Planning robotic missions in environments shared by humans involves designing controllers that are reactive to the environment yet able to fulfill a complex high-level task. This paper introduces a new method for designing low-level controllers for nonlinear robotic platforms based on a discrete-state high-level controller encoding the behaviors of a reactive task specification. We build our method upon a new type of trajectory constraint which we introduce in this paper, reactive composition, to provide the guarantee that any high-level reactive behavior may be fulfilled at any moment during the continuous execution. We generate pre-computed motion controllers in a piecewise manner by adopting a sample-based synthesis method that associates a certificate of invariance with each controller in the sample set. As a demonstration of our approach, we simulate different robotic platforms executing complex tasks in a variety of environments.

Posted in: Robot motion planning

A nice review of the problem of kinematic modeling of wheeled mobile robots and a new approach that delays the use of coordinate frames

March 11, 2015 11:42 ,

Alonzo Kelly and Neal Seegmiller, 2015, Recursive kinematic propagation for wheeled mobile robots, The International Journal of Robotics Research, 34: 288-313, DOI: 10.1177/0278364914551773.

The problem of wheeled mobile robot kinematics is formulated using the transport theorem of vector algebra. Doing so postpones the introduction of coordinates until after the expressions for the relevant Jacobians have been derived. This approach simplifies the derivation while also providing the solution to the general case in 3D, including motion over rolling terrain. Angular velocity remains explicit rather than encoded as the time derivative of a rotation matrix. The equations are derived and can be implemented recursively using a single equation that applies to all cases. Acceleration kinematics are uniquely derivable in reasonable effort. The recursive formulation also leads to efficient computer implementations that reflect the modularity of real mechanisms.

Posted in: Robot models , Tagged: ,

A survey of semantic mapping for mobile robots

March 11, 2015 11:11 ,

Ioannis Kostavelis, Antonios Gasteratos, 2015, Semantic mapping for mobile robotics tasks: A survey, Robotics and Autonomous Systems, Volume 66, April 2015, Pages 86-103, ISSN 0921-8890, DOI: 10.1016/j.robot.2014.12.006.

The evolution of contemporary mobile robotics has given thrust to a series of additional conjunct technologies. Of such is the semantic mapping, which provides an abstraction of space and a means for human\u2013robot communication. The recent introduction and evolution of semantic mapping motivated this survey, in which an explicit analysis of the existing methods is sought. The several algorithms are categorized according to their primary characteristics, namely scalability, inference model, temporal coherence and topological map usage. The applications involving semantic maps are also outlined in the work at hand, emphasizing on human interaction, knowledge representation and planning. The existence of publicly available validation datasets and benchmarking, suitable for the evaluation of semantic mapping techniques is also discussed in detail. Last, an attempt to address open issues and questions is also made.

Posted in: Semantic maps for robots

Novel recursive bayesian estimator based on approaching pdfs by polynomials and keeping a hypothesis for each of its modes

February 10, 2015 20:08 ,

Huang, G.; Zhou, K.; Trawny, N.; Roumeliotis, S.I., (2015), A Bank of Maximum A Posteriori (MAP) Estimators for Target Tracking, Robotics, IEEE Transactions on , vol.31, no.1, pp.85,103. DOI: TRO.2014.2378432

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Nonlinear estimation problems, such as range-only and bearing-only target tracking, are often addressed using linearized estimators, e.g., the extended Kalman filter (EKF). These estimators generally suffer from linearization errors as well as the inability to track multimodal probability density functions. In this paper, we propose a bank of batch maximum a posteriori (MAP) estimators as a general estimation framework that provides relinearization of the entire state trajectory, multihypothesis tracking, and an efficient hypothesis generation scheme. Each estimator in the bank is initialized using a locally optimal state estimate for the current time step. Every time a new measurement becomes available, we relax the original batch-MAP problem and solve it incrementally. More specifically, we convert the relaxed one-step-ahead cost function into polynomial or rational form and compute all the local minima analytically. These local minima generate highly probable hypotheses for the target’s trajectory and hence greatly improve the quality of the overall MAP estimate. Additionally, pruning of least probable hypotheses and marginalization of old states are employed to control the computational cost. Monte Carlo simulation and real-world experimental results show that the proposed approach significantly outperforms the standard EKF, the batch-MAP estimator, and the particle filter.

Posted in: Mobile Robot Localization , Tagged: ,