2013 IEEE International Conference on Robotics and Automation

The main contribution of this paper is a new step-time controller for a vertically hopping robot leg capable of meeting a demanded step-time instantaneously, meaning within a single hop. The ability to perform hops of an arbitrary and changing size accurately forms the motivation behind the work done here. This would allow control of a running robot's foot placement and thus fast traversal of terr... View full abstract»

The use of free vibration in elastic structure can lead to energy efficient robot locomotion, since it significantly reduces the energy expenditure if properly designed and controlled. However, it is not well understood how to harness the dynamics of free vibration for the robot locomotion, because of the complex dynamics originated in discrete events and energy dissipation during locomotion. From... View full abstract»

This paper presents a 10 cm × 5 cm × 5 cm, 52 g one-motor driven robot. One DC motor with a driving gear drives two driven gears to implement the functions of jumping and walking. Two one-way bearings mounted on the inner races of the two driven gears are used to switch between jumping and walking when the motor rotates clockwise and anticlockwise respectively. The jumping energy is obtained by co... View full abstract»

This paper presents a six-legged, sprawl-tuned autonomous robot (STAR). This novel robot has a variable leg sprawl angle in the transverse plane to adapt its stiffness, height, and leg-to-surface contact angle. The sprawl angle can be varied from nearly positive 60 degrees to negative 90 degrees, enabling the robot to run in a planar configuration, upright, or inverted (see movie). STAR is fitted ... View full abstract»

Fleas have a unique catapult mechanism with a special muscle configuration. Energy is stored in an elastic material, resilin, and the extensor muscle. Force is applied by the extensor muscle to generate a torque. Energy is released as a small triggering muscle reverses the direction of the aforementioned torque. A flea can jump 150 times its body length using this elastic catapult mechanism. In th... View full abstract»

In this work, we propose a control scheme for attitude control of a falling, two link active tailed robot with only two degrees of freedom of actuation. We derive a simplified expression for the robot's angular momentum and invert this expression to solve for the shape velocities that drive the body's angular momentum to a desired value. By choosing a body angular velocity vector parallel to the a... View full abstract»

This paper describes a probabilistic surface matching method for pose-based bathymetry SLAM using a multibeam sonar profiler. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches. Then, a probabilistic implementation of the ICP is used to deal with the uncertainty of the robot pose as well as the measured points in a two-stage pr... View full abstract»

This paper proposes a navigation algorithm that provides a low-latency solution while estimating the full nonlinear navigation state. Our approach uses Sliding-Window Factor Graphs, which extend existing incremental smoothing methods to operate on the subset of measurements and states that exist inside a sliding time window. We split the estimation into a fast short-term smoother, a slower but ful... View full abstract»

In this paper, we demonstrate a system for temporally scalable visual SLAM using a reduced pose graph representation. Unlike previous visual SLAM approaches that maintain static keyframes, our approach uses new measurements to continually improve the map, yet achieves efficiency by avoiding adding redundant frames and not using marginalization to reduce the graph. To evaluate our approach, we pres... View full abstract»

Developing the perfect SLAM front-end that produces graphs which are free of outliers is generally impossible due to perceptual aliasing. Therefore, optimization back-ends need to be able to deal with outliers resulting from an imperfect front-end. In this paper, we introduce dynamic covariance scaling, a novel approach for effective optimization of constraint networks under the presence of outlie... View full abstract»

In this paper we defend the superior scalability of the Relative Bundle Adjustment (RBA) framework for tackling with the SLAM problem. Although such a statement was already done with the introduction of the sliding window (SW) solution to RBA [16], we claim that the map extension that can be maintained locally consistent for some fixed computational cost critically depends on the specific pattern ... View full abstract»

Partially-Observable Markov Decision Processes (POMDPs) are a problem class with significant applicability to robotics when considering the uncertainty present in the real world, however, they quickly become intractable for large state and action spaces. A method to create a less complex but accurate action model approximation is proposed and evaluated using a state-of-the-art POMDP solver. We app... View full abstract»

In this work, we develop a general solution to a broad class of grasping and manipulation problems that we term as C-SLAM for contact simultaneous localization and modeling, where the robots need to accurately track the motions of the contacted bodies and the locations of contacts, while simultaneously estimating important system parameters, such as body dimensions, masses and friction coefficient... View full abstract»

Powered prosthetic hands are becoming increasingly functional through sensory feedback. However, when using electrical stimulation as sensory feedback for electromyographic (EMG) prosthetics, stimulation artifacts may cause EMG data noise. Electrical stimulation and EMG measurements are therefore performed using time-division methods in rehabilitation facilities. Under time-division methods, EMG l... View full abstract»

This paper introduces a tactile or contact method whereby an autonomous robot equipped with suitable sensors can choose the next sensing action involving touch in order to accurately localize an object in its environment. The method uses an information gain metric based on the uncertainty of the object's pose to determine the next best touching action. Intuitively, the optimal action is the one th... View full abstract»

The fusion of tactile and visual modalities is crucial for understanding objects and learning how to manipulate them. A common modus operandi in robotics is to deal with each of these modalities separately. We propose an integrated approach that associates to local visual features of an object, tactile feedback of the effector when touching that part of the object. Thus the agent learns to predict... View full abstract»

The perception of the surrounding world depends on noisy sensors which introduce uncertainty. When we develop algorithms for grasping with robotic hands it is not enough to assume the best estimate of the environment - if there is a measure of uncertainty we need to account for it. This paper presents a control law which augments a grasp controller with the ability to prefer known or unseen region... View full abstract»

This paper develops an estimation framework for sensor-guided dual-arm manipulation of a rigid object. Using an unscented Kalman Filter (UKF), the approach combines both visual and kinesthetic information to track both the manipulators and object. From visual updates of the object and manipulators, and tactile updates, the method estimates both the robot's internal state and the object's pose. Non... View full abstract»

The ability to search visually for objects of interest in cluttered environments is crucial for robots performing tasks in a multitude of environments. In this work, we propose a novel visual search algorithm that integrates high-level information of the target object - specifically its size and shape, with a recently introduced visual operator that rapidly clusters potential edges based on their ... View full abstract»

We address the problem of image-based scene analysis from streaming video, as would be seen from a moving platform, in order to efficiently generate spatially and temporally consistent predictions of semantic categories over time. In contrast to previous techniques which typically address this problem in batch and/or through graphical models, we demonstrate that by learning visual similarities bet... View full abstract»

This work demonstrates how 3D qualitative spatial relationships can be used to improve object detection by differentiating between true and false positive detections. Our method identifies the most likely subset of 3D detections using seven types of 3D relationships and adjusts detection confidence scores to improve the average precision. A model is learned using a structured support vector machin... View full abstract»

With the availability of cheap and powerful RGB-D sensors interest in 3D point cloud based methods has drastically increased. One common prerequisite of these methods is to abstract away from raw point cloud data, e.g. to planar patches, to reduce the amount of data and to handle noise and clutter. We present a novel method to abstract RGB-D sensor data to parametric surface models described by B-... View full abstract»

We address the problem of clearing a pile of unknown objects using an autonomous interactive perception approach. Our robot hypothesizes the boundaries of objects in a pile of unknown objects (object segmentation) and verifies its hypotheses (object detection) using deliberate interactions. To guarantee the safety of the robot and the environment, we use compliant motion primitives for poking and ... View full abstract»

Transparent objects are ubiquitous in human environments but, due to their special interaction with light, very few vision methods exist to identify them. We propose a new algorithm for recognition and pose estimation of rigid transparent objects which can deal with overlapping instances and cluttered environments. Using an active depth sensor for segmentation of the objects and 2d edge analysis f... View full abstract»

Facial communicative signals (FCSs) such as head gestures, eye gaze, and facial expressions can provide useful feedback in conversations between people and also in human-robot interaction. This paper presents a pattern recognition approach for the interpretation of FCSs in terms of valence, based on the selection of discriminative subsequences in video data. These subsequences capture important te... View full abstract»