scholarly journals Passively safe partial motion planning for mobile robots with limited field-of-views in unknown dynamic environments

2014 ◽  
Author(s):  
S. Bouraine ◽  
Th. Fraichard ◽  
O. Azouaoui ◽  
Hassen Salhi
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Dynamic Environments ◽  
Passively Safe

Motion Planning of Mobile Robots for Occluded Obstacles

2018 ◽  
Vol 30 (3) ◽  
pp. 485-492
Author(s):  
Satoshi Hoshino ◽  
◽  
Tomoki Yoshikawa
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Dynamic Environments ◽  
Simulation Experiments ◽  
Moving Obstacles ◽  
Moving Direction ◽  
Velocity Obstacle

Motion planning of mobile robots for occluded obstacles is a challenge in dynamic environments. The occlusion problem states that if an obstacle suddenly appears from the occluded area, the robot might collide with the obstacle. To overcome this, we propose a novel motion planner, the Velocity Obstacle for occlusion (VOO). The VOO is based on a previous motion planner, the Velocity Obstacle (VO), which is effective for moving obstacles. In the proposed motion planner, information uncertainties about occluded obstacles, such as position, velocity, and moving direction, are quantitatively addressed. Thus, the robot based on the VOO is able to move not only among observed obstacles, but also among the occluded ones. Through simulation experiments, the effectiveness of the VOO for the occlusion problem is demonstrated by comparison with the VO.

scholarly journals Trend-aware motion planning for wheeled mobile robots operating in dynamic environments

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142092529
Author(s):  
Sheng Liu ◽  
Fengji Dai ◽  
Shaobo Zhang ◽  
Yangqing Wang ◽  
Zhenhua Wang
Keyword(s):  
Motion Estimation ◽  
Motion Planning ◽  
Mobile Robots ◽  
Dynamic Environments ◽  
Poor Quality ◽  
Motion Prediction ◽  
Optimization Approach ◽  
Elastic Band ◽  
Wheeled Mobile Robots

Planning collision-free trajectories is essential for wheeled mobile robots operating in dynamic environments safely and efficiently. Most current trajectory generation methods focus on achieving optimal trajectories in static maps and considering dynamic obstacles as static depending on the precise motion estimation of the obstacles. However, in realistic applications, dealing with dynamic obstacles that have low reliable motion estimation is a common situation. Furthermore, inaccurate motion estimation leads to poor quality of motion prediction. To generate safe and smooth trajectories in such a dynamic environment, we propose a motion planning algorithm called trend-aware motion planning (TAMP) for dynamic obstacle avoidance, which combines with timed-elastic band. Instead of considering dynamic obstacles as static, our planning approach predicts the moving trends of the obstacles based on the given estimation. Subsequently, the approach generates a trajectory away from dynamic obstacles, meanwhile, avoiding the moving trends of the obstacles. To cope with multiple constraints, an optimization approach is adopted to refine the generated trajectory and minimize the cost. A comparison of our approach against other state-of-the-art methods is conducted. Results show that trajectories generated by TAMP are robust to handle the poor quality of obstacles’ motion prediction and have better efficiency and performance.

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