9 accepted papers
Autonomous ground robots navigating unstructured off-road environments face perceptual challenges, such as sensor obscuration or failure, which can lead to inaccurate perception or navigation failures. While robot adaptation has recently gained increasing attention, self-reflective robot adaptation,
Autonomous navigation in unstructured environments is a challenging task due to the complex and dynamic nature of robot-terrain interactions. Existing approaches often struggle to generalize amidst the complexities of real-world settings. They tend to rely on hand-engineered, rule-based robot models…
Collaborative scheduling is an essential ability for a team of heterogeneous robots to collaboratively complete complex tasks, e.g., in a multi-robot assembly application. To enable collaborative scheduling, two key problems should be addressed, including allocating tasks to heterogeneous robots and…
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 uncer…
Acceptance of social robots in human-robot collaborative environments depends on the robots’ sensitivity to human moral and social norms. Robot behavior that violates norms may decrease trust and lead human interactants to blame the robot and view it negatively. Hence, for long-term acceptance, soci…
Terrain adaptation is a critical ability for a ground robot to effectively traverse unstructured off-road terrain in real-world field environments such as forests. However, the expected or planned maneuvering behaviors cannot always be accurately executed due to setbacks such as reduced tire pressur…
Place recognition is a critical component towards addressing the key problem of Simultaneous Localization and Mapping (SLAM). Most existing methods use visual images; whereas, place recognition using 3D point clouds, especially based on the voxel representations, has not been well addressed yet. In…
When a mobile robot is deployed in a field environment, e.g., during a disaster response application, the capability of adapting its navigational behaviors to unstructured terrains is essential for effective and safe robot navigation. In this paper, we introduce a novel joint terrain representation…
Over the recent years, long-term place recognition has attracted an increasing attention to detect loops for largescale Simultaneous Localization and Mapping (SLAM) in loopy environments during long-term autonomy. Almost all existing methods are designed to work with traditional cameras with a limit…