waashk/dblp huggingface dataset:
mapping, navigation, and learning for off-road traversal. the challenge in the darpa learning applied to ground robots (lagr) project is to autonomously navigate a small robot using stereo vision as the main sensor. during this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision as the main sensor. the system is very robust&mdash;we can typically give it a goal position several hundred meters away and expect it to get there. in this paper we describe the main components that comprise the system, including stereo processing, obstacle and free space interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and control. at the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain. &copy; 2008 wiley periodicals, inc.
cad-based automated robot programming in adhesive spray systems for shoe outsoles and uppers. most shoe manufacturing processes are not yet automated; it puts restrictions on increasing productivity. among them, adhesive application processes particularly are holding the most workers and working hours. in addition, the working environment is very poor due to the toxicity of adhesive agents. in the case of automating an adhesive application process by using a robot, robot teaching by playback is difficult to produce high productivity because the kinds of shoes to be taught mount up to several thousands. to cope with it, it is necessary to generate robot working paths automatically according to the kind, the size, or the right and the left of shoes, and also to teach the generated paths to a robot automatically. this paper presents a method to generate three-dimensional robot working paths off-line based on cad data in an automatic adhesive spray system for shoe outsoles and uppers. first, this paper describes how to extract the three-dimensional data of an outsole outline from a two-dimensional cad drawing file. second, it describes how to extract the three-dimensional data of an upper profiling line from the three-dimensional scanning data that is opened in a three-dimensional cad program. third, it describes how to generate robot working paths based on the extracted data and the nozzle setting parameters for adhesive spray. also, a series of experiments for adhesive spray is performed to verify the effectiveness of the presented methods. this study will do much for increasing productivity in shoe manufacturing as a core work of a robotic adhesive spray system. &copy; 2004 wiley periodicals, inc.
adaptive steering control of a farm tractor with varying yaw rate properties. this paper presents a novel application of a model reference adaptive control (mrac) system to control the lateral position of a farm tractor tracking a straight path. farm tractors can be configured with various implements, and the tractor yaw rate dynamics vary with each implement. it is desired that the lateral position response of the farm tractor remain consistent with respect to different implement configurations. therefore, a mrac system is implemented on the farm tractor to compensate for yaw rate plant variations by adapting the feed-forward yaw rate controller. simulation results of the algorithm are shown that display poor performance due to neglected steering actuator dynamics and saturation. modifications are made to the algorithm to account for the steering actuator properties, and more simulated results are presented that display ideal performance. finally, the mrac algorithm is implemented on a john deere 8420 farm tractor, and experimental results are presented. &copy; 2009 wiley periodicals, inc.
driving with tentacles: integral structures for sensing and motion. in this paper we describe a lidar-based navigation approach applied at both the c-elrob (european land robot trial) 2007 and the 2007 darpa urban challenge. at the c-elrob 2007 the approach was used without any prior knowledge about the terrain and without global positioning system (gps). at the urban challenge the approach was combined with a gps-based path follower. at the core of the method is a set of &ldquo;tentacles&rdquo; that represent precalculated trajectories defined in the ego-centered coordinate space of the vehicle. similar to an insect's antennae or feelers, they fan out with different curvatures discretizing the basic driving options of the vehicle. we detail how the approach can be used for exploration of unknown environments and how it can be extended to combined gps path following and obstacle avoidance allowing safe road following in case of gps offsets. &copy; 2008 wiley periodicals, inc.
reactive navigation of multiple moving agents by collaborative resolution of conflicts. in navigation that involves several moving agents or robots that are not in possession of each other's plans, a scheme for resolution of collision conflicts between them becomes mandatory. a resolution scheme is proposed in this paper specifically for the case where it is not feasible to have a priori the plans and locations of all other robots, robots can broadcast information between one another only within a specified communication distance, and a robot is restricted in its ability to react to collision conflicts that occur outside of a specified time interval called the reaction time interval. collision conflicts are resolved through velocity control by a search operation in the robot's velocity space. the existence of a cooperative phase in conflict resolution is indicated by a failure of the search operation to find velocities in the individual velocity space of the respective robots involved in the conflict. a scheme for cooperative resolution of conflicts is modeled as a search in the joint velocity space of the robots involved in conflict when the search in the individual space yields a failure. the scheme for cooperative resolution may further involve modifying the states of robots not involved in any conflict. this phenomenon is characterized as the propagation phase where cooperation spreads to robots not directly involved in the conflict. apart from presenting the methodology for the resolution of conflicts at various levels (individual, cooperative, and propagation), the paper also formally establishes the existence of the cooperative phase during real-time navigation of multiple mobile robots. the effect of varying robot parameters on the cooperative phase is presented and the increase in requirement for cooperation with the scaling up of the number of robots in a system is also illustrated. simulation results involving several mobile robots are presented to indicate the efficacy of the proposed strategy. &copy; 2005 wiley periodicals, inc.
magnebike: a magnetic wheeled robot with high mobility for inspecting complex-shaped structures. this paper describes the magnebike robot, a compact robot with two magnetic wheels in a motorbike arrangement, which is intended for inspecting the inner casing of ferromagnetic pipes with complex-shaped structures. the locomotion concept is based on an adapted magnetic wheel unit integrating two lateral lever arms. these arms allow for slight lifting off the wheel in order to locally decrease the magnetic attraction force when passing concave edges, as well as laterally stabilizing the wheel unit. the robot has the main advantage of being compact (180 &times; 130 &times; 220 mm) and mechanically simple: it features only five active degrees of freedom (two driven wheels each equipped with an active lifter stabilizer and one steering unit). the paper presents in detail design and implementation issues that are specific to magnetic wheeled robots. low-level control functionalities are addressed because they are necessary to control the active system. the paper also focuses on characterizing and analyzing the implemented robot. the high mobility is shown through experimental results: the robot not only can climb vertical walls and follow circumferential paths inside pipe structures but it is also able to pass complex combinations of 90-deg convex and concave ferromagnetic obstacles with almost any inclination regarding gravity. it requires only limited space to maneuver because turning on the spot around the rear wheel is possible. this high mobility enables the robot to access any location in the specified environment. finally the paper analyzes the maximum payload for different types of environment complexities because this is a key feature for climbing robots and provides a security factor about the risk of falling and slipping. &copy; 2009 wiley periodicals, inc.
optimal robot arm control using the minimum variance model. models of human movement from computational neuroscience provide a starting point for building a system that can produce flexible adaptive movement on a robot. there have been many computational models of human upper limb movement put forward, each attempting to explain one or more of the stereotypical features that characterize such movements. while these models successfully capture some of the features of human movement, they often lack a compelling biological basis for the criteria they choose to optimize. one that does provide such a basis is the minimum variance model (and its extension&mdash;task optimization in the presence of signal-dependent noise). here, the variance of the hand position at the end of a movement is minimized, given that the control signals on the arm's actuators are subject to random noise with zero mean and variance proportional to the amplitude of the signal. since large control signals, required to move fast, would have higher amplitude noise, the speed-accuracy trade-off emerges as a direct result of the optimization process. we chose to implement a version of this model that would be suitable for the control of a robot arm, using an optimal control scheme based on the discrete-time linear quadratic regulator. this implementation allowed us to examine the applicability of the minimum variance model to producing humanlike movement. in this paper, we describe our implementation of the minimum variance model, both for point-to-point reaching movements and for more complex trajectories involving via points. we also evaluate its performance in producing humanlike movement and show its advantages over other optimization based models (the well-known minimum jerk and minimum torque-change models) for the control of a robot arm. &copy; 2005 wiley periodicals, inc.
robust vision-based underwater homing using self-similar landmarks. next-generation autonomous underwater vehicles (auvs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. this paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. these algorithms are applied to an auv with controllers developed for vision-based docking with the target. experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions. &copy; 2008 wiley periodicals, inc.
transmission line maintenance robots capable of crossing obstacles: state-of-the-art review and challenges ahead. power line inspection and maintenance already benefit from developments in mobile robotics. this paper presents a comprehensive review of the state of the art. it focuses on mobile robots designed to cross obstacles found on a typical transmission line while using the conductor as support for traveling. promising areas of research and development as well as challenges that remain to be solved are discussed with a view to developing fully autonomous technologies. maintenance tasks, including inspection and repairs, are identified as high-value applications in transmission live-line work. conclusions are drawn from experience, and the future of mobile robotics applied to transmission line maintenance is discussed. &copy; 2009 wiley periodicals, inc.
vision-based navigation through urban canyons. we address the problem of navigating unmanned vehicles safely through urban canyons in two dimensions using only vision-based techniques. two commonly used vision-based obstacle avoidance techniques (namely stereo vision and optic flow) are implemented on an aerial and a ground-based robotic platform and evaluated for urban canyon navigation. optic flow is evaluated for its ability to produce a centering response between obstacles, and stereo vision is evaluated for detecting obstacles to the front. we also evaluate a combination of these two techniques, which allows a vehicle to detect obstacles to the front while remaining centered between obstacles to the side. through experiments on an unmanned ground vehicle and in simulation, this combination is shown to be beneficial for navigating urban canyons, including t-junctions and 90-deg bends. experiments on a rotorcraft unmanned aerial vehicle, which was constrained to two-dimensional flight, demonstrate that stereo vision allowed it to detect an obstacle to the front, and optic flow allowed it to turn away from obstacles to the side. we discuss the theory behind these techniques, our experience in implementing them on the robotic platforms, and their suitability to the urban canyon navigation problem. &copy; 2009 wiley periodicals, inc.
toward elevated agrobotics: development of a scaled-down prototype for visually guided date palm tree sprayer. agricultural operations at great heights are typically laborious, expensive, and dangerous for human workers. spraying and pollinating date palm trees, for instance, is currently done manually by a team of several workers from a platform lifted 18 m or more above the ground. this method is extremely unsafe, and many accidents have occurred due to instability when the platform is in a lifted position. in this paper we present the concept of an autonomous field robot that will effectively and accurately spray and pollinate date clusters. a scaled-down prototype has been designed and consists of a visually controlled robotic arm that guides the jet of a mounted sprayer directly to the date clusters completely autonomously and from a short distance. rather than requiring an expensive dedicated platform, this robotic apparatus can be towed by a standard tractor operated by a single driver, with no human worker operating in the heights. this system can minimize risk of injury, significantly save manpower, and deliver the spray with maximum accuracy, thereby reducing chemical disposal. the spraying guidance system is based on a proportional controller that uses feedback from an image processing system combined with a small dead band. the system was modeled mathematically, and the effect of each component on overall performance was evaluated by simulation. results were used for tuning the experimental system controller parameters. experiments were performed to evaluate the tracking performance of the visually guided tracking system on a single tree and a 10-m-long runway at a distance of 6 m. these dimensions were inspired by the conditions at a typical orchard. during the experiment the sprayer was towed along the runway 19 times, during which the speed of the wagon was varied between 0.7 km-h (0.2 m-s) and 12 km-h (3.3 m-s). experimental results indicate that up to a wagon ve1ocity of 1.25 m-s the tracking error was reasonably low and stayed below 10 deg from the center of the target (typical date spraying speed is 1.1 m-s). however, at higher speeds the tracking quality reduced progressively and some drift (i.e., accumulated error) was noticed in the pan axis due to image processing speed. the simulations and experiments with a scaled-down prototype show feasibility of the presented method and demonstrate how this new approach facilitates more efficient high-altitude agricultural robotics. &copy; 2009 wiley periodicals, inc.
learning outdoor mobile robot behaviors by example. we present an implementation and analysis of a real-time, online, supervised learning system for nonparametrically learning behaviors from a human trainer on a mobile robot in outdoor environments. this approach enables a human operator to train and tune robot behaviors simply by driving the robot with a remote control. hand-designed behaviors for outdoor environments often require many parameters, and complicated behaviors can be difficult or impossible to specify with a manageable number of parameters. furthermore, their design requires knowledge of the robot's internal models and knowledge of the environment in which the behaviors will be used. in real-world scenarios, we can design new behaviors using our learning system much more quickly than we can write hand-crafted behaviors. we present the results of training the robot to execute several specialized and general-purpose behaviors, including traversing a slalom, staying near &ldquo;cover,&rdquo; navigating on paths, navigating in an obstacle field, and general-purpose navigation. our system learns and executes most of these behaviors well after 1&ndash;4 h of operator training time. in quantitative tests, the learned behavior is not as robust as a hand-crafted behavior but often completes obstacle courses more quickly. additionally, we identify the factors that influence the effectiveness of this approach and investigate the properties of the training data provided by the human trainer. on the basis of our analyses, we suggest future work to ensure sufficient training, handle conflicting training examples, model robot dynamics, and further investigate dimensionality reduction of perception features. &copy; 2009 wiley periodicals, inc.
terrain adaptive navigation for planetary rovers. this paper describes the design, implementation, and experimental results of a navigation system for planetary rovers called terrain adaptive navigation (tanav). this system was designed to enable greater access to and more robust operations within terrains of widely varying slippage. the system achieves this goal by using onboard stereo cameras to remotely classify surrounding terrain, predict the slippage of that terrain, and use this information in the planning of a path to the goal. this navigation system consists of several integrated techniques: goodness map generation, terrain triage, terrain classification, remote slip prediction, path planning, high-fidelity traversability analysis, and slip-compensated path following. results from experiments with an end-to-end onboard implementation of the tanav system in a mars analog environment are shown and compared to results from experiments with a more traditional navigation system that does not account for terrain properties. &copy; 2009 wiley periodicals, inc.
global planning on the mars exploration rovers: software integration and surface testing. in january 2004, nasa's twin mars exploration rovers (mers), spirit and opportunity, began searching the surface of mars for evidence of past water activity. to localize and approach scientifically interesting targets, the rovers employ an onboard navigation system. given the latency in sending commands from earth to the martian rovers (and in receiving return data), a high level of navigational autonomy is desirable. autonomous navigation with hazard avoidance (autonav) is currently performed using a local path planner called gestalt (grid-based estimation of surface traversability applied to local terrain) that incorporates terrain and obstacle information generated from stereo cameras. gestalt works well at guiding the rovers around narrow and isolated hazards; however, it is susceptible to failure when clusters of closely spaced, nontraversable rocks form extended obstacles. in may 2005, a new technology task was initiated at the jet propulsion laboratory to address this limitation. specifically, a version of the field d* global path planner was integrated into mer flight software, enabling simultaneous local and global planning during autonav. a revised version of autonav was then uploaded to the rovers during the summer of 2006. in this paper we describe how this integration of global planning into the mer flight software was performed and provide results from both the mer surface system test bed rover and five fully autonomous runs by opportunity on mars. &copy; 2009 wiley periodicals, inc.
image-based path planning for outdoor mobile robots. mobile robots operating in natural terrain need some sort of long-range perception in order to navigate efficiently. whereas ladar is a commonly used sensor on such systems, providing range data out to 25 m and beyond, we have instead focused on what information can be extracted from vision. our robot has only two stereo camera pairs for terrain sensing; they provide reliable stereo data up to 5 m away, but this is not enough to prevent myopic behavior. to overcome this problem, we have developed a novel approach to navigation using monocular imagery by planning a path in the image space. we take a monocular image and apply a learned color-to-cost mapping to transform the raw image into a cost image. then, after a pseudo-configuration-space transform, we search for a pixel-to-pixel path from a point in front of the robot to the projected goal point in the cost image. our implementation has been shown to react to obstacles at a range of 93 m, far beyond the range of our stereo perception. we describe the details of our method and results from testing under the darpa learning applied to ground robots (lagr) program and discuss the characteristics and trade-offs of our approach. &copy; 2009 wiley periodicals, inc.
autonomous off-road navigation with end-to-end learning for the lagr program. we describe a fully integrated real-time system for autonomous off-road navigation that uses end-to-end learning from onboard proprioceptive sensors, operator input, and stereo cameras to adapt to local terrain and extend terrain classification into the far field to avoid myopic behavior. the system consists of two learning algorithms: a short-range, geometry-based local terrain classifier that learns from very few proprioceptive examples and is robust in many off-road environments; and a long-range, image-based classifier that learns from geometry-based classification and continuously generalizes geometry to appearance, making it effective even in complex terrain and varying lighting conditions. in addition to presenting the learning algorithms, we describe the system architecture and results from the learning applied to ground robots (lagr) program's field tests. &copy; 2008 wiley periodicals, inc.