scholarly journals A new gap-based obstacle avoidance approach: follow the obstacle circle method

Robotica ◽  
2021 ◽  
pp. 1-24
Author(s):  
Hosein Houshyari ◽  
Volkan Sezer
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Robots ◽  
Circle Method ◽  
Path Following ◽  
Avoidance Task ◽  
The Real ◽  
Goal State ◽  
Challenging Tasks ◽  
Equidistant Points ◽  
Center Angle

Abstract One of the most challenging tasks for autonomous robots is avoiding unexpected obstacles during their path following operation. Follow the gap method (FGM) is one of the most popular obstacle avoidance algorithms that recursively guides the robot to the goal state by considering the angle to the goal point and the distance to the closest obstacles. It selects the largest gap around the robot, where the gap angle is calculated by the vector to the midpoint of the largest gap. In this paper, a novel obstacle avoidance procedure is developed and applied to a real fully autonomous wheelchair. This proposed algorithm improves the FGM’s travel safety and brings a new solution to the obstacle avoidance task. In the proposed algorithm, the largest gap is selected based on gap width. Moreover, the avoidance angle (similar to the gap center angle of FGM) is calculated considering the locus of the equidistant points from obstacles that create obstacle circles. Monte Carlo simulations are used to test the proposed algorithm, and according to the results, the new procedure guides the robot to safer trajectories compared with classical FGM. The real experimental test results are in parallel to the simulations and show the real-time performance of the proposed approach.

scholarly journals Quadrotor Path Following and Reactive Obstacle Avoidance with Deep Reinforcement Learning

2021 ◽  
Vol 103 (4) ◽  
Author(s):  
Bartomeu Rubí ◽  
Bernardo Morcego ◽  
Ramon Pérez
Keyword(s):  
Reinforcement Learning ◽  
Obstacle Avoidance ◽  
Low Cost ◽  
Path Following ◽  
The State ◽  
Gradient Algorithm ◽  
Avoidance Task ◽  
Learning Approaches ◽  
Reward Function ◽  
Novel Structure

AbstractA deep reinforcement learning approach for solving the quadrotor path following and obstacle avoidance problem is proposed in this paper. The problem is solved with two agents: one for the path following task and another one for the obstacle avoidance task. A novel structure is proposed, where the action computed by the obstacle avoidance agent becomes the state of the path following agent. Compared to traditional deep reinforcement learning approaches, the proposed method allows to interpret the training process outcomes, is faster and can be safely trained on the real quadrotor. Both agents implement the Deep Deterministic Policy Gradient algorithm. The path following agent was developed in a previous work. The obstacle avoidance agent uses the information provided by a low-cost LIDAR to detect obstacles around the vehicle. Since LIDAR has a narrow field-of-view, an approach for providing the agent with a memory of the previously seen obstacles is developed. A detailed description of the process of defining the state vector, the reward function and the action of this agent is given. The agents are programmed in python/tensorflow and are trained and tested in the RotorS/gazebo platform. Simulations results prove the validity of the proposed approach.

Estimation of the severity of damage produced by a transverse crack

2020 ◽  
Vol 65 (1) ◽  
pp. 137-144
Author(s):  
Marius-Vasile Pop
Keyword(s):  
Transverse Crack ◽  
Bending Moment ◽  
Cantilever Beams ◽  
Trend Line ◽  
The Real ◽  
Symmetrical Deformation ◽  
Frequency Drop ◽  
Equidistant Points ◽  
Fixed End ◽  
Crack Position

This paper presents a method to find the severity of a crack for cantilever beams that can be used to estimate the frequency drop due to the crack. The severity is found for the crack located at the location where the biggest curvature (or bending moment) is achieved. Because the fixing condition does not permit a symmetrical deformation around the crack, the apparent severity is smaller as the real one. The latter is found by the estimated value of the trend-line at the fixed end, it being constructed on points that consider the crack position (equidistant points in the proximity of the fixed end) and the resulted deflections.

scholarly journals Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4374
Author(s):  
Jose Bernardo Martinez ◽  
Hector M. Becerra ◽  
David Gomez-Gutierrez
Keyword(s):  
Obstacle Avoidance ◽  
Tracking Control ◽  
Global Coordinate System ◽  
Avoidance Task ◽  
Time Varying ◽  
Control Laws ◽  
Formation Tracking ◽  
Control Scheme ◽  
First Time ◽  
Hierarchical Scheme

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.

scholarly journals A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping

Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Peng Xu ◽  
Xingyu Wang ◽  
Siyuan Wang ◽  
Tianyu Chen ◽  
Jianhua Liu ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Robots ◽  
Tactile Sensor ◽  
Triboelectric Nanogenerator ◽  
Tactile Sensors ◽  
Biologically Inspired ◽  
External Stimulation ◽  
Autonomous Surface Vehicles ◽  
Electrostatic Induction ◽  
Contact Position

Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor’s applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.

Motion Analysis of Human Lifting Works with Heavy Objects

2005 ◽  
Vol 17 (6) ◽  
pp. 628-635 ◽  
Author(s):  
Nobutomo Matsunaga ◽  
◽  
Shigeyasu Kawaji
Keyword(s):  
Motion Control ◽  
Motion Analysis ◽  
Real World ◽  
Control Strategy ◽  
Robot Control ◽  
Autonomous Robots ◽  
Biped Robot ◽  
Weight Lifting ◽  
The Real ◽  
Lower Back

Advances in robot development involves autonomous work in the real world, where robots may lift or carry heavy objects. Motion control of autonomous robots is an important issue, in which configurations and motion differ depending on the robot and the object. Isaka et al. analyzed that lifting configuration is important in realizing efficient lifting minimizing the burden on the lower back, but their analysis was limited to weight lifting of a fixed object. Biped robot control requires analyzing different lifting in diverse situations. Thus, motion analysis is important in clarifying control strategy. We analyzed dynamics of human lifting of barbells in different situations, and found that lifting can be divided into four motions.

Multi-Sensor Fusion Based Effective Obstacle Avoidance and Path-Following Technology

2014 ◽  
Vol 20 (10) ◽  
pp. 1751-1756 ◽  
Author(s):  
Byambaa Dorj ◽  
Doopalam Tuvshinjargal ◽  
KilTo Chong ◽  
Dong Pyo Hong ◽  
Deok Jin Lee
Keyword(s):  
Obstacle Avoidance ◽  
Sensor Fusion ◽  
Path Following
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