text: Autonomous exploration of unknown environments has been widely applied in inspection, surveillance, and search and rescue. In exploration task, the basic requirement for robots is to detect the unknown space as fast as possible. In this paper, we propose an autonomous collaborative system consists of an aerial robot and a ground vehicle to explore in unknown environments. We combine the frontier based method and the harmonic field to generate a path. Then, For the ground robot, a minimum jerk piecewise Bezier curve which can guarantee safety and dynamical feasibility is generated amid obstacles. For the aerial robot, a motion primitive method is adopted for local path planning. We implement the proposed framework on an autonomous collaborative aerial-ground system. Extensive field experiments as well as simulations are presented to validate the method and demonstrate its higher efficiency against each single vehicle.
  @cite_0: Collaboration between heterogeneous robots can greatly improve the overall robot system by obtaining capabili­ties that each single robot is unable to achieve. In this paper, we present a collaborative robot system designed for search and rescue missions in an unknown environment with obstacles. The system consists of an aerial robot and a ground robot. An extended Kalman filter (EKF) is used for robot pose estimation, and an online trajectory generation algorithm is implemented for dynamic obstacle avoidance of the ground robot. The aerial robot first surveys an area of interests and sources a number of targets. The ground robot is then guided by the aerial robot to reach the target location while at the same time avoids obstacles along the way using a laser range finder. The system is entirely autonomous, achieves maximum efficiency and releases the human operator from all low-level types of operations. A centralized EKF is implemented with the flexibility of easily being modified into a distributed EKF.
  @cite_8: Exploring and mapping previously unknown environments while avoiding collisions with obstacles is a fundamental task for autonomous robots. In scenarios where this needs to be done rapidly, multi-rotors are a good choice for the task, as they can cover ground at potentially very high velocities. Flying at high velocities, however, implies the ability to rapidly plan trajectories and to react to new information quickly. In this paper, we propose an extension to classical frontier-based exploration that facilitates exploration at high speeds. The extension consists of a reactive mode in which the multi-rotor rapidly selects a goal frontier from its field of view. The goal frontier is selected in a way that minimizes the change in velocity necessary to reach it. While this approach can increase the total path length, it significantly reduces the exploration time, since the multi-rotor can fly at consistently higher speeds.
  @cite_2: We introduce a new approach for exploration based on the concept of frontiers, regions on the boundary between open space and unexplored space. By moving to new frontiers, a mobile robot can extend its map into new territory until the entire environment has been explored. We describe a method for detecting frontiers in evidence grids and navigating to these frontiers. We also introduce a technique for minimizing specular reflections in evidence grids using laser-limited sonar. We have tested this approach with a real mobile robot, exploring real-world office environments cluttered with a variety of obstacles. An advantage of our approach is its ability to explore both large open spaces and narrow cluttered spaces, with walls and obstacles in arbitrary orientation.
summary: Exploration of unknown environments using autonomous robots has been considered as a fundamental problem in robotics applications such as search and rescue @cite_0 , industrial inspection and 3D modelling. For exploration, the basic requirement for robots is to scan unknown space or detect free space as fast as possible. UGV (unmanned ground vehicle) @cite_2 and UAV (unmanned aerial vehicle) @cite_8 both have been employed for such a task with differences primarily in: (1) UGVs are more payload-capable. A ground vehicle can carry heavy, long-range laser scanners which are inapplicable for weight-constrained UAVs; (2) UAVs have superiors mobility and agility. UAV can fly above obstacles and cover areas that are inaccessible to UGVs, like obstacle's top surfaces. Consequently, a UGV often enjoys a larger sensor-coverage, yet cluttered and view-blocking environments could hamper its performance; on the other hand, a UAV may deliver inferior exploration efficiency due to its short-range sensor, but enjoys unblocked downward-looking view. Therefore, UGV favors open areas while UAV prefers cluttered places.