Contribution 

• A probing-driven navigation framework to prevent robots from remaining trapped when obstacles cannot be reliably perceived or even in perception-denied scenarios;

• The design of an abstract forest simulation environment to develop and systematically evaluate our probing-driven navigation framework;

•  Experimental validation of the proposed framework both in simulation and in real-world forest scenarios with two different robot platforms.

Trial Scenarios in Forest Environments

• The blue point and arrow mark the starting position and orientation;

• The yellow line indicates the destination line;

• The inset image highlights the main obstacles with red lines. 

 Abstract Forest Simulations 

• Representative examples from 500 abstract forest simulation environments;

• Each environment spans a 50 x 50 m area with a tree density of 80 trees/hectare, where each tree has a radius of 0.25m;

• Black lines indicate fallen branches, green circles represent stating trees and red dots mark the locations where the robot becomes immobilized or slips on rough terrain accidentally ;

• The green line shows the robot’s trajectory. The red star indicates the starting point and the black arrow denotes the designated heading. 

Simulation Results 

• 1000 experiments for each algorithm;

• 500 random generated simulation environments;

• 2 experiments in each environment with different random seed.

Real Forest Experiments

Forest Escape Challenge

• 45 m shortest distance from the starting point to the destination line (paved pathway);

•  Multiple challenging scenarios during the trial;

Supplementary Materials

Impact of Robot Dimension on Performance

• 1000 experiments in 500 randomly generated simulation environments;

• Limited effects on performance when the size of robots changes;

• MiniRover: 200 mm x 200 mm

• ForestRover: 400 mm x 400 mm

Impact of Fixed Turning Angle on Performance

• 1000 experiments in 500 randomly generated simulation environments;

• Performance evaluated with Forest-Pledge;

• Performance is better within the range between 10 to 50 degrees.

• Performance is robust within the range between 10 to 50 degrees.  

Detailed Visualization of Runs in Trial Scenarios in Real Forests

• Gray bars: Escape time

• Brown bars: Entrapment trials

• Red Vertical lines: Human interventions