Multi-Objective Risk Assessment Framework for Exploration Planning Using Terrain and Traversability Analysis

TL;DR

This work proposes a multi-objective risk assessment method for exploration planning in unconstrained environments that ensures consistent exploration without incurring lethal actions, while introducing minimal computational overhead to the planning process.

Abstract

Exploration of unknown, unstructured environments, such as in search and rescue, cave exploration, and planetary missions,presents significant challenges due to their unpredictable nature. This unpredictability can lead to inefficient path planning and potential mission failures. We propose a multi-objective risk assessment method for exploration planning in such unconstrained environments. Our approach dynamically adjusts the weight of various risk factors to prevent the robot from undertaking lethal actions too early in the mission. By gradually increasing the allowable risk as the mission progresses, our method enables more efficient exploration. We evaluate risk based on environmental terrain properties, including elevation, slope, roughness, and traversability, and account for factors like battery life, mission duration, and travel distance. Our method is validated through experiments in various subterranean simulated cave environments. The results demonstrate that our approach ensures consistent exploration without incurring lethal actions, while introducing minimal computational overhead to the planning process.

Figures (8)

• Figure 1: Trajectory of the agent in DARPA Subterranean Cave World 1 Environment utilizing the risk assessment framework while exploration planning using terrain analysis from onboard sensor measurements
• Figure 2: Illustration of the sensor data and the various layers of the terrain map used to assign a risk factor to the robots at a certain position in the environment.
• Figure 3: Raincloud plots present the average Perceived Risk by the agents for 10 runs each in Darpa Cave 1 for 1800 seconds with risk-aware planning (red) and without the risk assessment framework (blue)
• Figure 4: Raincloud plots present the average Perceived Risk by the agents for 10 runs each in Darpa Cave 2 for 600 seconds with risk-aware planning (red) and without the risk assessment framework (blue)
• Figure 5: Raincloud plots present the average Perceived Risk by the agents for 10 runs each in Darpa Cave 1 for 600 seconds with risk-aware planning (red) and without the risk assessment framework (blue)