Obstacle Avoidance Strategy Research Articles

Effects of task constraints on obstacle avoidance strategies in patients with cerebellar disease

The present study examined the effects of cerebellar disease on the organization and execution of obstacle avoidance tasks. To this end, we characterized how variations in the execution demands of the subsequent obstacles in multiple obstacle crossing tasks influenced the stepping performance of the initial obstacle in patients with cerebellar degeneration (CD) by manipulating the height (6cm and 16cm) and distance (1m and 2m) of the second obstacle. Nine patients with bilateral cerebellar atrophy and nine age-matched normal controls were instructed to walk along an 8m long pathway and step over two obstacles without contacting them. The primary finding indicated that CD patients exhibited an elevated foot clearance over the initial obstacle when the height demand of the second obstacle was increased. Such abnormal step-height adjustments in CD patients are considered as an adaptive avoidance strategy to diminish the execution demands of complex obstacle tasks and to enhance safe performance. These results suggest that the cerebellum is important for the implementation of optimal stepping strategies to be used during multiple obstacle crossings in which the obstacles have different execution demands.

Healthy younger and older adults control foot placement to avoid small obstacles during gait primarily by modulating step width

BackgroundFalls are a significant problem in the older population. Most falls occur during gait, which is primarily regulated by foot placement. Variability of foot placement has been associated with falls, but these associations are inconsistent and generally for smooth, level flooring. This study investigates the control of foot placement and the associated gait variability in younger and older men and women (N=7/group, total N=28) while walking at three different speeds (slow, preferred, and fast) across a control surface with no obstacles and surfaces with multiple (64) small (10cm long ×13mm high) visible and hidden obstacles.ResultsMinimum obstacle distance between the shoe and nearest obstacle during each footfall was greater on the visible obstacles surface for older subjects because some of them chose to actively avoid obstacles. This obstacle avoidance strategy was implemented primarily by modulating step width and to a lesser extent step length as indicated by linear regressions of step width and length variability on minimum obstacle distance. Mean gait speed, step length, step width, and step time did not significantly differ by subject group, flooring surface, or obstacle avoidance strategy.ConclusionsSome healthy older subjects choose to actively avoid small obstacles that do not substantially perturb their gait by modulating step width and, to a lesser extent, step length. It is not clear if this obstacle avoidance strategy is appropriate and beneficial or overcautious and maladaptive, as it results in fewer obstacles encountered at a consequence of a less efficient gait pattern that has been shown to indicate increased fall risk. Further research is needed on the appropriateness of strategy selection when the environmental demands and/or task requirements have multiple possible completion strategies with conflicting objectives (i.e. perceived safety vs. efficiency).

Robust On-line Obstacle Detection using Range Data for Reactive Navigation

Abstract This paper proposes a robust on-line and adaptive elliptic trajectory for reactive obstacle avoidance. These trajectories permit a safe and smooth mobile robot navigation in cluttered environment. Indeed, they use limit-cycle principle already applied in the literature Adouane et al. (2011). The main contribution proposed here is to perform this navigation in a completely reactive way while using only uncertain range data. Each obstacle, in this obstacle avoidance strategy, is surrounded by an ellipse and its parameters are obtained online while using the sequence of uncertain range data. This method uses the fusion between heuristic approach and Extended Kalman Filter (EKF) techniques to improve the computed ellipse parameters. A large number of simulations and experiments show the efficiency of the proposed on-line navigation in cluttered environment.

A Behaviour-Based Architecture for Mapless Navigation Using Vision

Autonomous robots operating in an unknown and uncertain environment must be able to cope with dynamic changes to that environment. For a mobile robot in a cluttered environment to navigate successfully to a goal while avoiding obstacles is a challenging problem. This paper presents a new behaviour-based architecture design for mapless navigation. The architecture is composed of several modules and each module generates behaviours. A novel method, inspired from a visual homing strategy, is adapted to a monocular vision-based system to overcome goal-based navigation problems. A neural network-based obstacle avoidance strategy is designed using a 2-D scanning laser. To evaluate the performance of the proposed architecture, the system has been tested using Microsoft Robotics Studio (MRS), which is a very powerful 3D simulation environment. In addition, real experiments to guide a Pioneer 3-DX mobile robot, equipped with a pan-tilt-zoom camera in a cluttered environment are presented. The analysis of the results allows us to validate the proposed behaviour-based navigation strategy.

Can a Simple Control Scheme Work for a Formation Control of Multiple Autonomous Underwater Vehicles?

The proportional and derivative (PD) and proportional, integral, and derivative (PID) controllers have been used extensively in industry due to their simplicity and effectiveness. This paper aims to investigate whether simple PD and adaptive PD-based controllers work for a complex system consisting of a group of multiple autonomous underwater vehicles (AUVs). Simple control laws with exact and uncertain gravity compensation are proposed for shape control of multiple AUVs. The proposed adaptive PD-based controller, in the presence of gravity uncertainty, requires only the model of gravity and buoyancy regressor matrix and does not require any knowledge of the inertia matrix, Coriolis and centripetal force, hydrodynamic damping and the parameters of the gravity, and buoyancy forces of the AUVs. Hence, the proposed controllers have the advantages of simplicity and ease of implementation. A novel collision and obstacle avoidance strategy using multi-layer region control concept, which limit the unnecessary use of high control efforts that lead to oscillatory movements of AUVs, is discussed. Lyapunov-like functions are proposed for the stability analysis. Simulation studies on AUVs with 6 degrees-of-freedom are presented to demonstrate the effectiveness of the proposed controllers.

Strategy and Realization for Obstacle Avoidance of Wheeled Mobile Robots Based on Dynamic Modeling

Wheeled mobile robot is a typical non-integral system. The non-integral constraints of the system make the dynamics modeling and trajectory tracing more difficult. In the study and development of a wheeled mobile robot prototype SDLG-C, aiming at the characteristics of the non-integral constraints, the dynamics model has been built with the Newton-Euler method by directly integrate the non-integral constraints into the dynamics equations. Consequently, the Obstacle avoidance effects of the high frequency disturbance on the performances of the control system have been eliminated. Based on the behavior–based robot control technology, the intelligent avoiding barriers control system design of an autonomous mobile robot is presented. And the implementation technology of this scheme is introduced; Simulations and experiments are processed to evaluate the proposed algorithm. Both of them have successfully verified the feasibility of the modeling and the effectiveness of the Obstacle avoidance strategy.

A robust navigation system for robotic wheelchairs

A landmark based navigation system for robotic wheelchairs is developed. The proposed navigation system is robust in the localization procedure which is the major problem in robotic navigation systems. Every landmark is composed of a segment of metallic path and a radio-frequency identification (RFID) tag. The odometry information is used for localization, which is corrected on-line every time the robotic wheelchair is over a landmark. A topological map is generated using such landmarks to compute the shortest path. A technique to generate the topological map for this navigation system and an obstacle avoidance strategy are also developed.

Type-2 Fuzzy Control of a Mobile Robot for Avoiding Moving Object

This research utilizes type-2 fuzzy logic system to a wheeled mobile robot (WMR) for moving object avoidance. A CCD camera and a localization system are integrated in the control scheme. The wheeled mobile robot can adjust moving path by the position and heading angle, which are given from the localization system. Dynamic obstacle avoidance strategy is implemented in fuzzy rules. Distance between the WMR and an obstacle, center coordinate, heading angle, and displacement of the obstacle can all be obtained by image process and distance computation algorithm. Experiments show that the WMR can perform dynamic obstacle avoidance successfully.

UAV Optimal Obstacle Avoidance while Respecting Target Arrival Specifications

AbstractEffective target tracking and obstacle avoidance strategies are essential to the success of unmanned aerial vehicle (UAV) missions. This paper describes a decentralized model-based predictive control to calculate the optimal UAV trajectory that will lead each UAV to the interception of a target at a desired time and with desired speed, heading and flight path angle, while avoiding dynamic ellipsoidal obstacles detected en route. Obstacle avoidance is based on the minimization of the UAV collision probability with all known obstacles on a future horizon, while ensuring that the collision probability with any given obstacle at each prediction step does not surpass a preset threshold. Cooperation between UAVs is possible by exchanging information about the obstacles they detect. To respect the arrival specifications, a virtual target is created and tracked. The virtual target moves at the desired speed and along a straight line that is correctly oriented to intercept the real target position at the desired arrival time. Arrival specifications are respected if tracking of the virtual target by the UAV is successful. Simulations are presented to demonstrate the effectiveness of the proposed approach. They also illustrate that cooperation can improve the UAV performance.

Unmanned Aerial Vehicle Optimal Cooperative Obstacle Avoidance in a Stochastic Dynamic Environment

DOI: 10.2514/1.50800 Effective target-tracking and obstacle avoidance strategies are essential to the success of unmanned aerial vehicle missions. This paper presents an extended Kalman-filter-based algorithm that predicts the optimal threedimensional trajectory and position prediction error of a dynamic object (obstacle or target) detected by an unmanned aerial vehicle. This trajectory prediction scheme is thereafter tested in a three-dimensional path planner for multiple unmanned aerial vehicles, which relies on decentralized model-based predictive control to calculate the optimal unmanned aerial vehicle setpoints that will lead each unmanned aerial vehicle to the interception of a single dynamic ellipsoidal target while avoiding dynamic ellipsoidal obstacles detected en route. A novel model-based predictive control collision avoidance algorithm is also presented in this paper. The method first computes the unmanned aerial vehicle collision probability with an obstacle by convolving the statistical distribution of the obstacle center of mass position with the obstacle shape. The method then seeks to minimize the unmanned aerial vehicle collision probability with all known obstacles on a future horizon, all while ensuring that the collision probability with any given obstacle at each prediction step does not surpass a preset threshold. Simulations are presented to demonstrate the effectiveness of the proposed approach.

Letter Posting and Orientation Matching: Two Equivalent Tasks in Action and Perception?

The finding that in a patient with visual form agnosia (DF), the performance level varies in a visuomotor letter-posting task and a perceptual orientation matching task was considered as part of the evidence for the perception-action model (Milner and Goodale, 1995). In this study we examined an alternative interpretation of these findings. We specifically tested whether orientation matching and letter posting can be accomplished using different strategies. Sixteen neurologically intact participants were asked to either put cards of different sizes through a target slot of a certain orientation or to simply indicate the slot's orientation. Letter-posting was performed in three different conditions varying the amount of visual feedback available. Results show that some participants apply a strategy of obstacle-avoidance in the posting task. That is, they oriented the card such that the safety margin between the edges of the target and the card was increased. This tendency became stronger with increasing card size. In contrast, in the orientation matching task, the end-orientation of the card was unaffected by its size and closer to the slot's actual orientation. The findings suggest that posting and matching can be solved using different visuo-spatial information. The perception-action dissociation reported for these tasks in DF might therefore simply indicate a difficulty in computing visual orientation, an ability that is needed for successful orientation matching but not for posting.

Dynamic Formation Control for Multiple Robots in Uncertain Environments

A novel dynamic formation control approach for multiple robots in uncertain environments is proposed, which adopts the formation parameter matrix to establish the relative relationship among the robots, transforms the global-level formation control problem into the problem that the-off-axis point of the follower tracks the-off-axis point on the virtual robot which has the same orientation with the leader robot and maintains the desired relative distance and desired observation angle with respect to its leader robot. The control law based on the derived error tracking system model about the follower and leader is designed to maintain the formation, and an obstacle avoidance strategy is proposed to prevent the robot from possible collisions with obstacles and other robots. Simulation results are given to demonstrate the feasibility and effectiveness of the approach.

A Multi-robot Dynamic Following Approach Based on Local Sensing

摘要: 主要研究了未知环境中的多机器人系统的无碰协调跟随问题, 提出了一种跟随机器人的基于局部感知的多模式控制方法, 分为到达、旋转角度调整、跟随、避障和随机搜索五种模式, 其中跟随模式采用模糊距离调整与角度调整策略实现对领航机器人的跟随并尽量与之保持一定的距离, 当需要避障时, 切线约束的避障策略使得自主机器人安全躲避潜在的危险. 该方法降低了多机器人系统对通讯的依赖性, 易于扩展, 通过实验对有效性进行了验证. 关键词: 多机器人 / 动态跟随 / 局部感知 / 多模式控制

Velocity dependence of optic flow strategy for steering and obstacle avoidance

Velocity dependence of optic flow strategy for steering and obstacle avoidance

FORMATION CONTROL AND SWITCHING FOR MULTIPLE ROBOTS IN UNCERTAIN ENVIRONMENTS

A novel formation control and switching approach for multiple robots in uncertain environments is proposed in this paper. A formation parameter matrix is adopted to establish the relative relationship among the robots, and the formation control problem is converted into the tracking problem of the-off-axis point of the follower to the-off-axis point on the virtual robot, which has the same orientation as that of the leader and maintains a desired relative distance and desired observation angle with respect to the leader. The tracking control law is then designed. An obstacle avoidance strategy combined with formation switching is proposed to avoid collisions in the presence of obstacles, and a fault tolerance strategy is given to deal with the situations when some robots are broken. Simulation results are given to demonstrate the validity of the proposed approach.

Fast reinforcement learning for simple physical robots

In the past few years, the field of autonomous robot has been rigorously studied and non-industrial applications of robotics are rapidly emerging. One of the most interesting aspects of this field is the development of the learning ability which enables robots to autonomously adapt to given environments without human guidance. As opposed to the conventional methods of robots’ control, where human logically design the behavior of a robot, the ability to acquire action strategies through some learning processes will not only significantly reduce the production costs of robots but also improves the applicability of robots in wider tasks and environments. However, learning algorithms usually require large calculation cost, which make them unsuitable for robots with limited resources. In this study, we propose a simple two-layered neural network that implements a novel and fast Reinforcement Learning. The proposed learning method requires significantly less calculation resources, hence is applicable to small physical robots running in the real world environments. For this study, we built several simple robots and implemented the proposed learning mechanism to them. In the experiments, to evaluate the efficacy of the proposed learning mechanism, several robots were simultaneously trained to acquire obstacle avoidance strategies in the same environment, thus, forming a dynamic environment where the learning task is substantially harder than in the case of learning in a static environment and promising result was obtained.

Three-Dimensional Obstacle Avoidance Strategies for Uninhabited Aerial Systems Mission Planning and Replanning

The ability to perform autonomous mission planning is considered one of the key enabling technologies for uninhabited aerial systems. Subsequently, a big effort is made in the development of algorithms capable of computing safe and efficient routes in terms of distance, time, and fuel. In this paper an innovative 3-D planning algorithm is presented. The algorithm is based on considering the uninhabited aerial systems representation of real world systems as objects moving in a virtual environment (terrain, obstacles, and no fly zones), which replicates the airspace. Original obstacle avoidance strategies have been conceived to generate mission plans that are consistent with flight rules and with the vehicle performance constraints. Simulation test results show that efficient routes are computed in a few seconds.

Dynamic model based formation control and obstacle avoidance of multi-robot systems

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

Vision-Based Obstacle Detection and Avoidance: Application to Robust Indoor Navigation of Mobile Robots

We propose a more practical and efficient method for obstacle detection and avoidance. In this paper, a robot detects obstacles based on the projective invariants of stereo cameras, fuses this information with two-dimensional scanning sensor data, and finally builds up a more informative and conservative occupancy map. Although this approach is not supposed to recognize the exact shape of the obstacles, this shortcoming is overcome in the actual application by its fast calculation time and robustness against the illumination conditions. To avoid detected obstacles, a new reactive obstacle avoidance strategy is also presented. To evaluate the proposed method, we applied it to the mobile robot iMARO-III. In this test, iMARO-III has succeeded in long-term operation for 7 days continuously without any intervention of engineers and any collision in the real office environment.

Age-related changes in avoidance strategies when negotiating single and multiple obstacles

The aim of this research was to describe age-related changes in locomotor adjustments during obstructed gait and expand and build from the current body of literature describing single obstacle avoidance strategies by including trials in which the subjects stepped over two identical obstacles placed in series. We observed young adults (YA: N = 8; aged 23.1 +/- 2.0 years) and older adults (OA: N = 8; aged 76.1 +/- 4.3 years) as they walked along a 5 m long instrumented pathway (GAITRite) and stepped over one or two obstacles that were scaled to their lower leg length. Infrared markers, tracked using the Optotrak motion analysis system (60 Hz; Northern Digital Inc, Canada), were fixed to subjects' trunk and feet, and several anatomical landmarks were digitized for each segment (e.g. toes). Data analyses included lead and trail toe clearance values, take-off and landing distance, step time, length, width and velocity, and three-dimensional trunk angles. Both age groups were able to successfully complete the obstacle avoidance task, and the presence of a second obstacle did not affect clearance strategies of either OA or YA. OA crossed the obstacles with a reduced step velocity and stepped closer to the trailing edge, although take-off distances were not different between the age groups. Additionally, OA used similar ranges of trunk motion as YA when crossing the obstacle, but did so while using smaller step lengths and step widths compared to YA, effectively, using a narrower base of support. Together, these findings suggest that older adults adopted a more cautious crossing strategy in that they reduced their crossing step velocity. However, other aspects of the avoidance strategy used by the older adults, specifically the shortened landing distances and the use of similar ranges of trunk motion within a narrowed BOS, could potentially put them at risk for tripping or imbalance when stepping over an obstacle.