Group Multi-Object Tracking for Dynamic Risk Map and Safe Path Planning

2021 ◽  
Author(s):  
Lyuyu Shen ◽  
Hongliang Guo ◽  
Yechao Bai ◽  
Lei Qin ◽  
Marcelo Ang ◽  
...  
Keyword(s):  
Path Planning ◽  
Object Tracking ◽  
Risk Map ◽  
Dynamic Risk ◽  
Safe Path

Safe Path Planning with Gaussian Process Regulated Risk Map

2019 ◽  
Author(s):  
Hongliang Guo ◽  
Zehui Meng ◽  
Zefan Huang ◽  
Leong Wei Kang ◽  
Ziyue Chen ◽  
...  
Keyword(s):  
Path Planning ◽  
Gaussian Process ◽  
Risk Map ◽  
Safe Path

scholarly journals Safe Path Planning Algorithms for Mobile Robots Based on Probabilistic Foam

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4156
Author(s):  
Luís B. P. Nascimento ◽  
Dennis Barrios-Aranibar ◽  
Vitor G. Santos ◽  
Diego S. Pereira ◽  
William C. Ribeiro ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Configuration Space ◽  
Autonomous Robot ◽  
Breadth First Search ◽  
Propagation Process ◽  
Robot Systems ◽  
And Performance ◽  
Safe Path ◽  
High Clearance

The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies.

Safe Path Planning with Multi-Model Risk Level Sets

2020 ◽  
Author(s):  
Zefan Huang ◽  
Wilko Schwarting ◽  
Alyssa Pierson ◽  
Hongliang Guo ◽  
Marcelo Ang ◽  
...  
Keyword(s):  
Path Planning ◽  
Level Sets ◽  
Risk Level ◽  
Model Risk ◽  
Safe Path

scholarly journals Time-efficient path planning using two virtual robots

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141988674
Author(s):  
Jonghoek Kim
Keyword(s):  
Path Planning ◽  
Finite Time ◽  
Free Space ◽  
Path Length ◽  
Optimal Path ◽  
Three Dimensional ◽  
Computational Time ◽  
Topological Map ◽  
Planning Algorithms ◽  
Safe Path

This article introduces time-efficient path planning algorithms handling both path length and safety within a reasonable computational time. The path is planned considering the robot’s size so that as the robot traverses the constructed path, it doesn’t collide with an obstacle boundary. This article introduces two virtual robots deploying virtual nodes which discretize the obstacle-free space into a topological map. Using the topological map, the planner generates a safe and near-optimal path within a reasonable computational time. It is proved that our planner finds a safe path to the goal in finite time. Using MATLAB simulations, we verify the effectiveness of our path planning algorithms by comparing it with the rapidly-exploring random tree (RRT)-star algorithm in three-dimensional environments.

Safe path planning for free-floating space robot to approach noncooperative spacecraft

2017 ◽  
Vol 232 (7) ◽  
pp. 1258-1271 ◽  
Author(s):  
Fuhai Zhang ◽  
Yili Fu ◽  
Shan Zhu ◽  
He Liu ◽  
Bin Guo ◽  
...  
Keyword(s):  
Path Planning ◽  
Orbital Plane ◽  
Planning Method ◽  
Space Robot ◽  
Autonomous Rendezvous ◽  
Simulation Results ◽  
Target Satellite ◽  
Safe Path

In order to eliminate plume impingement on the target satellite, a free-floating space robot (also known as a chaser), which has the advantage of executing on-orbit service, is always used. This paper develops a path planning method for a safe rendezvous of chaser with a noncooperative target satellite in orbital coordinates. Safety principles for rendezvous in terminal approaching phase are proposed. Grasp points on the target satellite are analyzed and classified into two categories, and a moving ellipse trajectory is adopted to approach a rotating and uncontrolled target satellite. This method guarantees that the chaser can successfully escape if unexpected error occurs or capture fails. The simulation results show that, with this novel autonomous rendezvous method, the chaser can approach the noncooperative target satellite along the designated trajectory in any quadrant of the orbital plane.

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