Subterranean environments, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies with complex terrain, and perceptually degraded conditions. Such settings present challenges to autonomous information gathering for aerial and ground platforms alike. In response to the above, this study details a set of path planning methods tailored to the problem of autonomous exploration using aerial and ground robots, including the task of combined volumetric mapping and simultaneous visual search. The first part of this thesis presents an exploration path planner unified across aerial and ground robots. The method builds upon a graph-based exploration path planning scheme and focuses on a) enabling ...
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems...
Many applications of autonomous robots depend on the robot being able to navigate in real world envi...
This paper proposes a motion planning strategy for reconfigurable mobile robots in uneven terrain. P...
Autonomous robotic exploration is expanding into an ever-increasing set of critical applications inc...
Autonomous exploration of subterranean environments remains a major challenge for robotic systems. I...
In this work, we present an adaptive behavior path planning method for autonomous exploration and vi...
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments ...
In this paper we present the complete system design for an aerial robot capable of autonomous explor...
In this work the challenge of autonomous exploration and mapping in underground environments using a...
This kind of robot is capable to perform many modes of locomotion. This skill allows them to adapt...
We address the problem of planning a path for a ground robot through unknown terrain, using observat...
In this thesis, two deep learning-based path planning methods for autonomous exploration of subterra...
Deploying robots in unknown and complex areas for inspection tasks is becoming a real need for vario...
This thesis presents a multi-robot exploration path planning framework for underground environments,...
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems...
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems...
Many applications of autonomous robots depend on the robot being able to navigate in real world envi...
This paper proposes a motion planning strategy for reconfigurable mobile robots in uneven terrain. P...
Autonomous robotic exploration is expanding into an ever-increasing set of critical applications inc...
Autonomous exploration of subterranean environments remains a major challenge for robotic systems. I...
In this work, we present an adaptive behavior path planning method for autonomous exploration and vi...
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments ...
In this paper we present the complete system design for an aerial robot capable of autonomous explor...
In this work the challenge of autonomous exploration and mapping in underground environments using a...
This kind of robot is capable to perform many modes of locomotion. This skill allows them to adapt...
We address the problem of planning a path for a ground robot through unknown terrain, using observat...
In this thesis, two deep learning-based path planning methods for autonomous exploration of subterra...
Deploying robots in unknown and complex areas for inspection tasks is becoming a real need for vario...
This thesis presents a multi-robot exploration path planning framework for underground environments,...
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems...
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems...
Many applications of autonomous robots depend on the robot being able to navigate in real world envi...
This paper proposes a motion planning strategy for reconfigurable mobile robots in uneven terrain. P...