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When robots operate in real-world off-road environments with unstructured terrains, the ability to adapt their navigational policy is critical for effective and safe navigation. However, off-road terrains introduce several challenges to robot navigation, including dynamic obstacles and terrain uncertainty, leading to inefficient traversal or navigation failures. To address these challenges, we introduce a novel approach for adaptation by negotiation that enables a ground robot to adjust its navigational behaviors through a negotiation process. Our approach first learns prediction models for various navigational policies to function as a terrain-aware joint local controller and planner. Then, through a new negotiation process, our approach learns from various policies' interactions with the environment to agree on the optimal combination of policies in an online fashion to adapt robot navigation to unstructured off-road terrains on the fly. Additionally, we implement a new optimization algorithm that offers the optimal solution for robot negotiation in real-time during execution. Experimental results have validated that our method for adaptation by negotiation outperforms previous methods for robot navigation, especially over unseen and uncertain dynamic terrains. 

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot’s actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method’s performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques. 

Abstract Directed cell migration in complex micro-environments, such as in vivo pores, is important for predicting locations of artificial tissue growth and optimizing scaffold architectures. Yet, the directional decisions of cells facing multiple physiochemical cues have not been characterized. Hence, we aim to provide a ranking of the relative importance of the following cues to the decision-making of individual fibroblast cells: chemoattractant concentration gradient, channel width, mitosis, and contact-guidance. In this study, bifurcated micro-channels with branches of different widths were created. Fibroblasts were then allowed to travel across these geometries by following a gradient of platelet-derived growth factor-BB (PDGF-BB) established inside the channels. Subsequently, a combination of statistical analysis and image-based diffusion modeling was used to report how the presence of multiple complex migration cues, including cell-cell influences, affect the fibroblast decision-making. It was found that the cells prefer wider channels over a higher chemoattractant gradient when choosing between asymmetric bifurcated branches. Only when the branches were symmetric in width did the gradient become predominant in directing which path the cell will take. Furthermore, when both the gradient and the channels were symmetric, contact guidance became important for guiding the cells in making directional choices. Based on these results we were able to rank these directional cues from most influential to the least as follows: mitosis > channel width asymmetry > chemoattractant gradient difference > and contact-guidance. It is expected that these results will benefit the fields of regenerative medicine, wound healing and developmental biology.