Showing papers on "Obstacle avoidance published in 2006"

Fly-inspired visual steering of an ultralight indoor aircraft

Abstract: We aim at developing autonomous microflyers capable of navigating within houses or small indoor environments using vision as the principal source of information. Due to severe weight and energy constraints, inspiration is taken from the fly for the selection of sensors, for signal processing, and for the control strategy. The current 30-g prototype is capable of autonomous steering in a 16/spl times/16 m textured environment. This paper describes models and algorithms which allow for efficient course stabilization and collision avoidance using optic flow and inertial information.

A probabilistic approach to optimal robust path planning with obstacles

Abstract: Autonomous vehicles need to plan trajectories to a specified goal that avoid obstacles. Previous approaches that used a constrained optimization approach to solve for finite sequences of optimal control inputs have been highly effective. For robust execution, it is essential to take into account the inherent uncertainty in the problem, which arises due to uncertain localization, modeling errors, and disturbances. Prior work has handled the case of deterministically bounded uncertainty. We present here an alternative approach that uses a probabilistic representation of uncertainty, and plans the future probabilistic distribution of the vehicle state so that the probability of collision with obstacles is below a specified threshold. This approach has two main advantages; first, uncertainty is often modeled more naturally using a probabilistic representation (for example in the case of uncertain localization); second, by specifying the probability of successful execution, the desired level of conservatism in the plan can be specified in a meaningful manner. The key idea behind the approach is that the probabilistic obstacle avoidance problem can be expressed as a disjunctive linear program using linear chance constraints. The resulting disjunctive linear program has the same complexity as that corresponding to the deterministic path planning problem with no representation of uncertainty. Hence the resulting problem can be solved using existing, efficient techniques, such that planning with uncertainty requires minimal additional computation. Finally, we present an empirical validation of the new method with a number of aircraft obstacle avoidance scenarios.

Autonomous Navigation and Obstacle Avoidance for Unmanned Surface Vehicles

Abstract: The US Navy and other Department of Defense (DoD) and Department of Homeland Security (DHS) organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. In order for USVs to fill these roles, they must be capable of a relatively high degree of autonomous navigation. Space and Naval Warfare Systems Center, San Diego is developing core technologies required for robust USV operation in a real-world environment, primarily focusing on autonomous navigation, obstacle avoidance, and path planning.

Robot-assisted wayfinding for the visually impaired in structured indoor environments

Abstract: We present a robot-assisted wayfinding system for the visually impaired in structured indoor environments. The system consists of a mobile robotic guide and small passive RFID sensors embedded in the environment. The system is intended for use in indoor environments, such as office buildings, supermarkets and airports. We describe how the system was deployed in two indoor environments and evaluated by visually impaired participants in a series of pilot experiments. We analyze the system's successes and failures and outline our plans for future research and development.

Systems and methods for obstacle avoidance

Abstract: Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Formation control for a cooperative multi-agent system using decentralized navigation functions

Abstract: We propose a decentralized cooperative controller for a group of mobile agents. The control design is based on the navigation function formalism. The aim of the group control law is to generate a pattern or formation in a given workspace while avoiding obstacles and collisions. The desired goal is specified in terms of distances among the agents. We show that it is always possible to design a control law as the gradient of a suitably-defined navigation function whose minimum corresponds to the desired configuration. Furthermore in certain cases, such as when the topology of the interconnection is an acyclic graph, this minimum is unique. Some simulations are shown to test the strategy.

Path planning and obstacle avoidance for autonomous mobile robots: a review

Abstract: Recent advances in the area of mobile robotics caused growing attention of the armed forces, where the necessity for unmanned vehicles being able to carry out the “dull and dirty” operations, thus avoid endangering the life of the military personnel. UAV offers a great advantage in supplying reconnaissance data to the military personnel on the ground, thus lessening the life risk of the troops. In this paper we analyze various techniques for path planning and obstacle avoidance and cooperation issues for multiple mobile robots. We also present a generic dynamics and control model for steering a UAV along a collision free path from a start to a goal position.

Control of adaptive locomotion: effect of visual obstruction and visual cues in the environment

Abstract: Visual information regarding obstacle position and size is used for planning and controlling adaptive gait. However, the manner in which visual cues in the environment are used in the control of gait is not fully known. This research examined the effect of obstacle position cues on the lead and trail limb trajectories during obstacle avoidance with and without visual information of the lower limbs and obstacle (termed visual exproprioception). Eight subjects stepped over obstacles under four visual conditions: full vision without obstacle position cues, full vision with position cues, goggles without position cues and goggles with position cues. Goggles obstructed visual exproprioception of the lower limbs and the obstacle. Position cues (2 m tall) were placed beside the obstacle to provide visual cues regarding obstacle position. Obstacle heights were 2, 10, 20 and 30 cm. When wearing goggles and without position cues, a majority of the dependent measures (horizontal distance, toe clearance and lead stride length) increased for the 10, 20 and 30 cm obstacles. Therefore lower limb–obstacle visual exproprioception was important for the control of both limbs, even though with normal vision the trail limb was not visible during obstacle clearance. When wearing goggles, the presence of position cues, which provided on-line visual exproprioception of the self relative to the obstacle position in the anterior–posterior direction, returned lead and trail foot placements to full vision values. Lead toe clearance was not affected by the position cues, trail clearance decreased but was greater than values observed during full vision. Therefore, visual exproprioception of obstacle location, provided by visual cues in the environment, was more relevant than visual exproprioception of the lower limbs for controlling lead and trail foot placement.

Conflict-free navigation in unknown urban environments

Abstract: This paper presents an autonomous exploration method in an unknown environment that uses model predictive control (MPC)-based obstacle avoidance with local map building by onboard sensing. An onboard laser scanner is used to build an online map of obstacles around the vehicle with outstanding accuracy. This local map is combined with a real-time MPC algorithm that generates a safe vehicle path, using a cost function that penalizes the proximity to the nearest obstacle. The adjusted trajectory is then sent to a position tracking layer in the hierarchical unmanned aerial vehicle (UAV) avionics architecture. In a series of experiments using a Berkeley UAV, the proposed approach successfully guided the vehicle safely through the urban canyon

Keep looking ahead? Re-direction of visual fixation does not always occur during an unpredictable obstacle avoidance task.

Abstract: Visual information about the environment, especially fixation of key objects such as obstacles, is critical for safe locomotion. However, in unpredictable situations where an obstacle suddenly appears it is not known whether central vision of the obstacle and/or landing area is required or if peripheral vision is sufficient. We examined whether there is a re-direction of visual fixation from an object fixated ahead to a suddenly appearing obstacle during treadmill walking. Furthermore, we investigated the temporal relationship between the onset of muscle activity to avoid the obstacle and saccadic eye and head movements to shift fixation. Eight females (mean ± SD; age = 24.8 ± 2.3 years) participated in this experiment. There were two visual conditions: a central vision condition where participants fixated on two obstacles attached to a bridge on the treadmill and a peripheral vision condition where participants fixated an object two steps ahead. There were two obstacle release conditions: only an obstacle in front of the left foot was released or an obstacle in front of either foot could be released. Only trials when the obstacle was released in front of the left foot were analyzed such that the difference in the two obstacle conditions was whether there was a choice of which foot to step over the obstacle. Obstacles were released randomly in one of three phases during the step cycle corresponding to available response times between 219 and 462 ms. We monitored eye and head movements along with muscle activity and spatial foot parameters. Performance on the task was not different between vision conditions. The results indicated that saccades are rarely made (< 18% of trials) and, when present, are initiated ∼ 350 ms after muscle activity for limb elevation, often accompanied by a downward head movement, and always directed to the landing area. Therefore, peripheral vision of a suddenly appearing obstacle in the travel path is sufficient for successful obstacle avoidance during locomotion: visual fixation is generally not re-directed to either the obstacle or landing area.

Maximizing miniature aerial vehicles

Abstract: Despite the tremendous potential demonstrated by miniature aerial vehicles (MAV) in numerous applications, they are currently limited to operations in open air space, far away from obstacles and terrain. To broaden the range of applications for MAVs, methods to enable operation in environments of increased complexity must be developed. In this article, we presented two strategies for obstacle and terrain avoidance that provide a means for avoiding obstacles in the flight path and for staying centered in a winding corridor. Flight tests have validated the feasibility of these approaches and demonstrated promise for further refinement

Formation Control of Underactuated Surface Vessels using the Null-Space-Based Behavioral Control

Abstract: In this paper the application of a behavior-based control approach, namely the Null-Space-based Behavioral control, to coordinate a fleet of autonomous surface vessels is presented. The NSB can be considered as a centralized guidance system aimed at driving the fleet in complex environments while simultaneously performing multiple tasks, i.e., obstacle avoidance or keeping a formation. In order to apply the guidance system to a fleet of underactuated surface vessels, the NSB works in combination with a low-level maneuvering control that, taking care of the dynamics of the vessels, elaborates the motion commands to generate the generalized forces at the actuators. The guidance system has been simulated in the accomplishment of a mission in presence of obstacles and sea current in the environment.

Obstacle avoiding apparatus, obstacle avoiding method, obstacle avoiding program and mobile robot apparatus

Abstract: The present invention provides an obstacle avoiding apparatus, an obstacle avoiding method, an obstacle avoiding program, and a mobile robot apparatus that can accurately model a robot apparatus and plan a highly precise moving route for the robot apparatus that avoids obstacles. The obstacle avoiding apparatus, to be used for a mobile robot apparatus to avoid obstacles, includes an obstacle environment map drawing section that divides the range of height from the reference surface for the mobile robot apparatus to move thereon to the height of the mobile robot apparatus into a plurality of layers corresponding to predetermined respective ranges of height and draws obstacle environment maps, each showing the condition of being occupied by one or more than one obstacles existing in the corresponding layer, and a route planning section that plans a route for the robot apparatus to move along according to an enlarged environment map prepared by enlarging the area occupied by the obstacle or obstacles in the obstacle environment maps as a function of the cross sectional profile of the mobile robot apparatus in each of the layers.

Robust hybrid controllers for continuous-time systems with applications to obstacle avoidance and regulation to disconnected set of points

Abstract: We give an elementary proof of the fact that, for continuous-time systems, it is impossible to use (even discontinuous) pure state feedback to achieve robust global asymptotic stabilization of a disconnected set of points or robust global regulation to a target while avoiding an obstacle. Indeed, we show that arbitrarily small, piecewise constant measurement noise can keep the trajectories away from the target. We give a constructive, Lyapunov-based hybrid state feedback that achieves robust regulation in the above mentioned settings.

Coordinated Maneuvering of Automated Vehicles in Platoons

Abstract: To eventually have automated vehicles operate in platoons, it is necessary to study what information each vehicle must have and to whom it must communicate for safe and efficient maneuvering in all possible conditions. This paper formulates the problem in terms of sensing and communicated information. By emulating platoons using a group of mobile robots, the authors demonstrate the feasibility of maneuvers (such as entering, exiting, and recuperating from an accident) using different distributed coordination strategies. The coordination strategies studied range from no communication to unidirectional or bidirectional exchanges between vehicles and to fully centralized decision by the leading vehicle. One particularity of this paper is that instead of assuming that the platoon leader or all vehicles globally monitor what is going on, only the vehicles involved in a particular maneuver are concerned, distributing decisions locally among the platoon. This paper reports experimental trials using robots having limited and directional perception of other things, using vision and obstacle avoidance sensing. Results confirm the feasibility of the coordination strategies in different conditions and various uses of communicated information to compensate for sensing limitations

Vision-based UAV flight control and obstacle avoidance

Abstract: In this work, we explore various ideas and approaches to deal with the inherent uncertainty and image noise in motion analysis, and develop a low-complexity, accurate and reliable scheme to estimate the motion fields from UAV navigation videos. The motion field information allows us to accurately estimate ego-motion parameters of the UAV and refine (or correct) the motion measurements from other sensors. Based on the motion field information, we also compute the range map for objects in the scene. Once we have accurate knowledge about the vehicle motion and its navigation environment (range map), control and guidance laws can be designed to navigate the UAV between way points and avoid obstacles.

Distributed Coordination of Simulated Robots Based on Self-Organization

Abstract: Distributed coordination of groups of individuals accomplishing a common task without leaders, with little communication, and on the basis of self-organizing principles, is an important research issue within the study of collective behavior of animals, humans, and robots. The article shows how distributed coordination allows a group of evolved, physically linked simulated robots (inspired by a robot under construction) to display a variety of highly coordinated basic behaviors such as collective motion, collective obstacle avoidance, and collective approach to light, and to integrate them in a coherent fashion. In this way the group is capable of searching and approaching a lighted target in an environment scattered with obstacles, furrows, and holes, where robots acting individually fail. The article shows how the emerged coordination of the group relies upon robust self-organizing principles (e.g., positive feedback) based on a novel sensor that allows the single robots to perceive the group's “average” motion direction. The article also presents a robust solution to a difficult coordination problem, which might also be encountered by some organisms, caused by the fact that the robots have to be capable of moving in any direction while being physically connected. Finally, the article shows how the evolved distributed coordination mechanisms scale very well with respect to the number of robots, the way in which robots are assembled, the structure of the environment, and several other aspects.

Characteristics of single and double obstacle avoidance strategies: a comparison between adults and children

Abstract: Activities of daily living often require us to negotiate several obstacles in the travel path. To date, there is little work investigating how adults accomplish such tasks, and there is even less known about multiple obstacle avoidance strategies used by children. The current work will expand our knowledge about the role of vision in adults and children when avoiding two obstacles placed in their travel path under altered ambient lighting. Healthy 7-year old children (n=10; aged 7.51+/-0.2 years) and adults (n=10; aged 22.76+/-1.7 years) were instrumented with infrared markers (Optotrak, NDI) placed on anatomical landmarks and asked to walk along a ten meter path under three conditions: unobstructed, single obstacle, or double obstacle. These trials were performed under two lighting conditions: Full (simulating standard office lighting) and Low (simulating a dark hallway lit by nightlights). Data analyses included lead and trail clearance values, step length, step width and step velocity, take-off distance and Horizontal toe Displacement at Apex (HDA) which was defined as the distance between the horizontal position of the toe to the leading edge of the obstacle when the toe reaches its peak height. Adults were able to maintain consistent behaviour regardless of the number of obstacles in the travel path. Children, however, adjusted their foot placement for the second obstacle. This indicates that having multiple obstacles in the travel path is a more challenging task for 7-year old, and suggests that children at this age may not have fully developed anticipatory locomotor strategies. Children had larger clearance values than adults for the lead foot crossing the obstacle under all obstacle and lighting conditions, and consistently used larger HDA values than adults. Together, these findings suggest that children adopt more cautious strategies than adults in complex environments. Additionally, children decreased walking velocity, increased step width and decreased their step length in a Low light environment. These changes are all indicators of a more careful avoidance strategy, which implies that children at this age rely heavily on visual information to guide foot placements in a complex environment.

Formation Control of Marine Surface Vessels Using the Null-Space-Based Behavioral Control

Abstract: In this paper the application of the Null-Space-Based behavioral control (NSB) to a fleet of marine surface vessels is presented. From a marine applications point of view, the NSB can be considered as a guidance system that dynamically selects the motion reference commands for each vessel of the fleet. These motion commands are aimed at guiding the fleet in complex environments simultaneously performing multiple tasks, i.e., obstacle avoidance or keeping a formation. In order to apply the guidance system to a fleet of surface vessels through the entire speed envelope (fully-actuated at low velocities, under-actuated at high velocities), the NSB works in combination with a low-level maneuvering control that, taking care of the dynamic models of the vessels, elaborates the motion commands to obtain the generalized forces at the actuators. The guidance system has been simulated while successfully performing complex missions in realistic scenarios.

Intact automatic avoidance of obstacles in patients with visual form agnosia

Abstract: In everyday life our reaching behaviour has to be guided not only by the location and properties of the target object, but also by the presence of potential obstacles in the workspace Recent evidence from neglect and optic ataxia patients has suggested that this automatic obstacle avoidance is mediated by the dorsal, rather than the ventral, stream of visual processing We tested this idea in two studies involving patients with visual form agnosia resulting from bilateral ventral-stream damage In the first study, we asked patient DF to reach out and pick up a target object in the presence of obstacles placed at varying distances to the left or right of the target We found that both DF and controls shifted their trajectories away from the potential obstacles and adjusted their grip aperture in such a way as to minimize risk of collision In a second study, we asked DF and a second patient, SB, to either reach between, or to bisect the space between, two cylinders presented at varying locations We found that both patients adjusted their reach trajectories to account for shifts in cylinder location in the reaching task, despite showing significantly worse performance than control subjects when asked to make a bisection judgement Taken together, these data indicate that automatic obstacle avoidance behaviour is spared in our patients with visual form agnosia We attribute their ability to the functional intactness of the dorsal stream of visual processing, and argue that the ventral stream plays no important role in automatic obstacle avoidance

Decentralized formation control and obstacle avoidance for multiple robots with nonholonomic constraints

Abstract: This paper proposes a formation control scheme for a group of mobile robots based on a multi-objective potential force. The angle of the potential force, with respect to the global coordinate system, is used to generate trajectories for the navigation of a group of nonholonomic mobile robots. A smooth and continuous control law, based on translational force input and rotational torque input, is designed to reduce the global orientation error asymptotically to zero while maintaining proper formation for a target configuration. Lyapunov stability theorem is applied to construct the proposed control with smooth continuous feedback, in which stability is proved for the control of multiple mobile robots. The formation regulation, flocking, and obstacle avoidance of the proposed control are validated through numerical simulation.

Local path planning using a new artificial potential function composition and its analytical design guidelines

Abstract: This paper presents a new framework for path planning based on artificial potential functions (APFs). In this scheme, the APFs for path planning have a multiplicative and additive composition between APFs for goal destination and APFs for obstacle avoidance, unlike conventional composition where the APF for obstacle avoidance is added to the APF for goal destination. In particular, this paper presents a set of analytical guidelines for designing potential functions to avoid local minima for a number of representative scenarios based on the proposed framework for path planning. Specifically the following cases are addressed: (i) a non-reachable goal problem (a case in which the potential of the goal is overwhelmed by the potential of an obstacle), (ii) an obstacle collision problem (a case in which the potential of the obstacle is overwhelmed by the potential of the goal) and (iii) a narrow passage problem (a case in which the potential of the goal is overwhelmed by the potential of two obstacles). The exa...

Obstacle Avoidance For Unmanned Air Vehicles Using Image Feature Tracking

Abstract: This paper discusses a computer vision algorithm and a control law for obstacle avoidance for small unmanned air vehicles using a video camera as the primary sensor. Small UAVs are used for low altitude surveillance ∞ights where unknown obstacles can be encountered. Small UAVs can be given the capability to navigate in uncertain environments if obstacles are identifled. This paper presents an obstacle detection methodology using feature tracking in a forward looking, onboard camera. Features are found using the Harris Corner Detector and tracked through multiple video frames which provides three dimensional localization of the salient features. A sparse three dimensional map of features provides a rough estimate of obstacle locations. The features are grouped into potentially problematic areas using agglomerative clustering. The small UAV then employs a sliding mode control law in the autopilot to avoid obstacles.

Anytime dynamic path-planning with flexible probabilistic roadmaps

Abstract: Probabilistic roadmaps (PRM) have been demonstrated to be very promising for planning paths for robots with high degrees of freedom in complex 3D workspaces. In this paper we describe a PRM path-planning method presenting three novel features that are useful in various real-world applications. First, it handles zones in the robot workspace with different degrees of desirability. Given the random quality of paths that are calculated by traditional PRM approaches, this provides a mean to specify a sampling strategy that controls the search process to generate better paths by simply annotating regions in the free workspace with degrees of desirability. Second, our approach can efficiently re-compute paths in dynamic environments where obstacles and zones can change shape or move concurrently with the robot. Third, it can incrementally improve the quality of a generated path, so that a suboptimal solution is available when required for immediate action, but get improved as more planning time is affordable

An agent-based simulation of pedestrian dynamics: from lane formation to auditorium evacuation

Abstract: In this paper we present an agent-based simulation of pedestrian dynamics based on cellular automata models. Differently from the cellular automata, our model represents different pedestrian characteristics: gender, speed, room geometry knowledge, and herding and obstacle avoidance behavior. We study how different room geometries, different pedestrian groups sizes and characteristics influence the pedestrian dynamics and the macroscopic behavior of the system. With this agent-based approach we expect to obtain more realistic results than the cases where the pedestrians are uniformly modeled. Our analysis indicates that pedestrian groups with different features contribute in different ways to the macroscopic behavior.

Spline-Based Robot Navigation

Abstract: This paper offers a path planning algorithm based on splines. The sought path avoids the obstacles, and is smooth and short. Smoothing is used as an integral part of the algorithm, and not only as a final improvement to a path found by other methods. In order to avoid a very difficult optimization over all the path's points, it is modeled by a sequence of splines defined by a gradually increasing number of knots.