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We present a fully integrated autonomous multirobot aerial system for finding and collecting moving and static objects with unknown locations. This task addresses multiple relevant problems in search and rescue (SAR) robotics such as multi-agent aerial exploration, object detection and tracking, and aerial gripping. Usually, the community tackles these problems individually but the integration into...
Learning from demonstration for motion planning is an ongoing research topic. In this paper we present a model that is able to learn the complex mapping from raw 2D-laser range findings and a target position to the required steering commands for the robot. To our best knowledge, this work presents the first approach that learns a target-oriented end-to-end navigation model for a robotic platform....
Localization is essential for robots to operate autonomously, especially for extended periods of time, when estimator drift tends to destroy alignment to any global map. Though there has been extensive work in vision-based localization in recent years, including several systems that show real-time performance, none have been demonstrated running entirely on-board in closed loop on robotic platforms...
For autonomous navigation of Micro Aerial Vehicles (MAVs) in cluttered environments, it is essential to detect potential obstacles not only in the direction of flight but in their entire local environment. While there exist systems that do vision based obstacle detection, most of them are limited to a single perception direction. Extending these systems to a multi-directional sensing approach would...
This paper presents a formalism that exploits deformability during manipulation of soft objects by robot teams. A hybrid centralized/distributed approach restricts centralized planning to high-level global guidance of the object for consensus. Low-level control is thus delegated to the individual manipulator robots, which retain manipulation and collision avoidance guarantees by passing forces to...
This paper presents a fast collision-detection method for sampling-based motion planners based on bounding volume hierarchies in workspace-time space. By introducing time as an additional dimension to the robot's workspace, the method is able to quickly evaluate time-indexed candidate trajectories for collision with the known future motions of other agents. The approach makes no assumptions on the...
This article describes an investigation of local motion planning, or collision avoidance, for a set of decision-making agents navigating in 3D space. The method is applicable to agents which are heterogeneous in size, dynamics and aggressiveness. It builds on the concept of velocity obstacles (VO), which characterizes the set of trajectories that lead to a collision between interacting agents. Motion...
This paper focuses on the problem of robust control of unmanned rotorcrafts against external disturbances, towards achieving their efficient and safe utilization in real-life challenging applications. Relying on state space representations that incorporate the effects of external disturbances and may be applied in most rotorcraft configurations, the basis for robust control is derived. Employing such...
The challenge of aerial robotic physical interaction towards inspection of infrastructure facilities through contact is the main motivation of this paper. A hybrid model predictive control framework is proposed, based on which a typical quadrotor vehicle becomes capable of stable physical interaction, accurate trajectory tracking on environmental surfaces as well as force control with only minor structural...
In this paper a centralized method for collision avoidance among multiple agents is presented. It builds on the velocity obstacle (VO) concept and its extensions to arbitrary kino-dynamics and is applicable to heterogeneous groups of agents (with respect to size, kino-dynamics and aggressiveness) moving in 2D and 3D spaces. In addition, both static and dynamic obstacles can be considered in the framework...
This paper presents a fully automated method to display objects and animations in 3D with a group of aerial vehicles. The system input is a single object or an animation (sequence of objects) created by an artist. The first stage is to generate physical goal configurations and robot colors to represent the objects with the available number of robots. The run-time system includes algorithms for goal...
In this paper a method for distributed reciprocal collision avoidance among multiple non-holonomic robots with bike kinematics is presented. The proposed algorithm, bicycle reciprocal collision avoidance (B-ORCA), builds on the concept of optimal reciprocal collision avoidance (ORCA) for holonomic robots but furthermore guarantees collision-free motions under the kinematic constraints of car-like...
This paper describes work on multi-robot pattern formation. Arbitrary target patterns are represented with an optimal robot deployment, using a method that is independent of the number of robots. Furthermore, the trajectories are visually appealing in the sense of being smooth, oscillation free, and showing fast convergence. A distributed controller guarantees collision free trajectories while taking...
The MagneBike robot is a magnetic wheeled robot designed for the inspection of ferromagnetic structures in power plants, especially steam chests. This video first presents the robot's locomotion concept, i.e. two aligned magnetic wheels integrating lateral lever arms, that allow the robot to pass over complex combinations of obstacles. Laboratory and field experiments show the high mobility of the...
One of the research areas that has received more and more interest during the last years is the development of driver assistant systems and semi-autonomous cars. However, densely populated environments like city centers are still a challenge for the operation of such systems. In this paper, we present approaches to two of the major tasks for autonomous driving in urban environments: self-localization...
Safe navigation through corridors plays a major role in the autonomous use of Micro Aerial Vehicles (MAVs) in indoor environments. In this paper, we present an approach for wall collision avoidance using a depth map based on optical flow from on board camera images. An omnidirectional fisheye camera is used as a primary sensor, while IMU data is needed for compensating rotational effects of the optical...
This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and modeling are combined with a smooth navigation function to perform on-line path planning in cluttered dynamic environments. The SLIP algorithm, an extension of iterative closest point, combines motion detection from a mobile platform with position estimation. This information is...
This paper focuses on development of a motion planning strategy for car-like vehicles in dynamic urban-like scenarios. The strategy can be summarized as a search for a collision-free trajectory among linearly moving obstacles applying rapidly-exploring random trees (RRT) and B-splines. Collision avoidance is based on geometric search in transformed state space of chained form kinematic model decomposition...
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