Motion Planning of Biped Robot Equipped with Stereo Camera Using Grid Map

2011 ◽  
Vol 5 (5) ◽  
pp. 639-647 ◽  
Author(s):  
Atsushi Yamashita ◽  
◽  
Masaaki Kitaoka ◽  
Toru Kaneko ◽  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Obstacle Avoidance ◽  
Biped Robot ◽  
Camera System ◽  
Biped Robots ◽  
Distance Information ◽  
Stereo Camera ◽  
Grid Map ◽  
Surrounding Environment

Recognizing its surroundings is important for biped robots seeking a destination. In this paper, we propose a motion planning method of a biped robot including path planning and obstacle avoidance. The robot obtains distance information on its surrounding environment from images captured by a stereo camera system, and generates a 3D map, then, builds a 2D grid map that locates flat floor regions, obstacle regions, bump regions, gate regions, and un-measured regions to decide its path by using the 2D grid map. Experimental results confirm the effectiveness of the proposed method.

Autonomous Path Planning of Space Manipulator for Capturing a Target Using Visual Information

2016 ◽  
Author(s):  
Yingzi Guan ◽  
Chunlin Song ◽  
Huijuan Dong
Keyword(s):  
Environmental Factors ◽  
Path Planning ◽  
Motion Planning ◽  
Visual Information ◽  
Planning Method ◽  
Moving Target ◽  
Camera System ◽  
Space Manipulator ◽  
Stereo Camera

In this work, we present a fast and reliable motion planning method for a free-floating manipulator considering various complex environmental factors. The proposed method employs a stereo camera system and hand-eye camera as sensors to measure position of a moving target. Simulation carried out in this work demonstrated the proposed method.

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

2018 ◽  
Vol 45 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Qiang Zhou ◽  
Danping Zou ◽  
Peilin Liu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Moving Objects ◽  
Point Clouds ◽  
Ultrasonic Sensor ◽  
Content Type ◽  
Stereo Camera ◽  
3D Point Clouds ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs. Findings The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects. Research limitations/implications The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV. Practical implications The developed approach could be valuable to applications in indoors. Originality/value This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

Hidden Attractor in a Passive Motion Model of Compass-Gait Robot

2018 ◽  
Vol 28 (14) ◽  
pp. 1850171 ◽  
Author(s):  
Mahdi Nourian Zavareh ◽  
Fahimeh Nazarimehr ◽  
Karthikeyan Rajagopal ◽  
Sajad Jafari
Keyword(s):  
Path Planning ◽  
Basin Of Attraction ◽  
Biped Robot ◽  
Motion Path ◽  
Motion Model ◽  
Hidden Attractor ◽  
Biped Robots ◽  
Sloping Surface ◽  
Dynamical Properties ◽  
Basin Of Attractions

Many studies have been done on different aspects of biped robots such as motion, path planning, control and stability. Dynamical properties of biped robot on a sloping surface such as equilibria and their stabilities, bifurcations and basin of attraction are investigated in this paper. Basin of attraction is an important property since it can determine the unseen conditions which affect the attractor of the system with multistabilities. By the help of basin of attractions, the paper claims that the strange attractors of compass-gait robot are hidden.

Research on a mobile manipulator for biochemical sampling tasks

2017 ◽  
Vol 44 (4) ◽  
pp. 467-478 ◽  
Author(s):  
Weidong Wang ◽  
Wenrui Gao ◽  
DongMei Wu ◽  
Zhijiang Du
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Gaussian Process ◽  
Obstacle Avoidance ◽  
Control Architecture ◽  
Content Type ◽  
Planning Strategy ◽  
Universal Control ◽  
Control Scheme ◽  
Avoidance Strategy

Purpose The paper aims to present a tracked robot comprised of several biochemical sampling instruments and a universal control architecture. In addition, a dynamic motion planning strategy and autonomous modules in sampling tasks are designed and illustrated at length. Design/methodology/approach Several sampling instruments with position tolerance and sealing property are specifically developed, and a robotic operation system (ROS)-based universal control architecture is established. Then, based on the system, two typical problems in sampling tasks, i.e. arm motion planning in unknown environment and autonomous modules, are discussed, implemented and tested. Inspired by the idea of Gaussian process classification (GPC) and Gaussian process (GP) information entropy, three-dimensional (3D) geometric modeling and arm obstacle avoidance strategy are implemented and proven successfully. Moreover, autonomous modules during sampling process are discussed and realized. Findings Smooth implementations of the two experiments justify the validity and extensibility of the robot control scheme. Furthermore, the former experiment proves the efficiency of arm obstacle avoidance strategy, while the later one demonstrates the time reduction and accuracy improvement in sampling tasks as the autonomous actions. Practical implications The proposed control architecture can be applied to more mobile and industrial robots for its feasible and extensible scheme, and the utility function in arm path planning strategy can also be utilized for other information-driven exploration tasks. Originality/value Several specific biochemical sampling instruments are presented in detail, while ROS and Moveit! are integrated into the system scheme, making the robot extensible, achievable and real-time. Based on the control scheme, an information-driven path planning algorithm and automation in sampling tasks are conceived and implemented.

Obstacle avoidance motion planning for mobile robots in a dynamic environment with moving obstacles

Robotica ◽  
1997 ◽  
Vol 15 (5) ◽  
pp. 493-510 ◽  
Author(s):  
Chia-Pin Wu ◽  
Tsu-Tian Lee ◽  
Chau-Ren Tsai
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Function Method ◽  
Dynamic Environment ◽  
Vector Form ◽  
Distance Information ◽  
Moving Obstacles ◽  
Simulation Results ◽  
Safe Path

A new real-time obstacle avoidance method for mobile robots has been developed. This method, namely the vector-distance function method, permits the detection of obstacles (both moving and stationary) and generates a path that can avoid collisions. The proposed approach expresses the distance information in a vector form. Then the notion of weighting is introduced to describe relationship between sensors of mobile robots and the target to be reached. Furthermore, R-mode, L-mode and T-mode are introduced to generate a safe path for the mobile robot in a dynamic environment filled with both stationary and moving obstacles. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. Simulation results are included to demonstrate the applicability and effectiveness of the developed algorithm.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

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