Automatic collision avoidance for manually tele-operated unmanned aerial vehicles

Israelsen, Jason; Beall, Matt; Bareiss, Daman; Stuart, Daniel; Keeney, Eric; Berg, Jur van den

doi:10.1109/icra.2014.6907839

Cited by 43 publications

(27 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous works [3] [10] [12] require a geometric representation of obstacle surfaces to represent obstacle avoidance constraints as linear inequalities of the form Ax ≤ b. While it is straightforward to use these inequality constraints to optimize a safe trajectory, it is non-trivial to find the normal and boundary of obstacle surfaces from real sensor data.…”

Section: A Environment Representation and Sensor Modelmentioning

confidence: 99%

High speed navigation for quadrotors with limited onboard sensing

Liu

Watterson

Tang

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

We address the problem of high speed autonomous navigation of quadrotor micro aerial vehicles with limited onboard sensing and computation. In particular, we propose a dual range planning horizon method to safely and quickly navigate quadrotors to specified goal locations in previously unknown and unstructured environments. In each planning epoch, a short-range planner uses a local map to generate a new trajectory. At the same time, a safe stopping policy is found. This allows the robot to come to an emergency halt when necessary. Our algorithm guarantees collision avoidance and demonstrates important advances in real-time planning. First, our novel short range planning method allows us to generate and re-plan trajectories that are dynamically feasible, comply with state and input constraints, and avoid obstacles in real-time. Further, previous planning algorithms abstract away the obstacle detection problem by assuming the instantaneous availability of geometric information about the environment. In contrast, our method addresses the challenge of using the raw sensor data to form a map and navigate in real-time. Finally, in addition to simulation examples, we provide physical experiments that demonstrate the entire algorithmic pipeline from obstacle detection to trajectory execution.

show abstract

Section: A Environment Representation and Sensor Modelmentioning

confidence: 99%

High speed navigation for quadrotors with limited onboard sensing

Liu

Watterson

Tang

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

show abstract

“…Although stable hover control (Azinheira & Moutinho, ; Hancer, Oner, Sirimoglu, & Unel, ) and collision avoidance (Israelsen et al., ; Ross et al.,, ) are an alternative approach for UAV control, we prefer the physical protection. This is because wind gusts around a bridge can be strong and may exceed limits of the control response.…”

Section: Introductionmentioning

confidence: 99%

Close visual bridge inspection using a UAV with a passive rotating spherical shell

Salaan

Okada

Mizutani

et al. 2018

Journal of Field Robotics

View full text Add to dashboard Cite

Today, robots are expected to be used for the inspection of infrastructures such as bridges. One important task in bridge inspection is to acquire clear images of its various parts for further damage evaluation. However, this task has not yet been completely realized because of the complexity of bridge structures. For this situation, a UAV with a passive rotating spherical shell (PRSS) that can easily maneuver while protecting itself is introduced. In this paper, we explain the development of the PRSS unmanned aerial vehicle (UAV) based on the design strategy. We then analyze its performance through simulated bridge inspection. Finally, we discuss the results of actual bridge experiments. The spherical shell has a size (D = 0.95 m) and structure (fullerene) that is well-suited for bridge inspection applications. It can also handle an impact equivalent to 2 m/s, which is more than the UAV's maximum flight speed. Test flight experiment also validated the characteristic of PRSS that shows a stable flight during disturbances. The image test also shows that the visual system can provide a full overhead view of the bridge. Likewise, it can detect a 0.1-mm wide line that replicates the damage (e.g., a crack) from a position 0.5 m away and while the camera moves at 0.3 m/s. These characteristics have yielded a system that can acquire inspection images from critical parts of the bridge. An evaluation by third parties confirmed the effectiveness of the system. Further, the system satisfies the mandatory requirements of the Next Generation Robots for Social Infrastructure (NGRSI) program.

show abstract

“…This method calculates the guidance law of avoidance manoeuvre according to the relative distance, speed, acceleration, angle, etc., between the aircraft and threats, but it is difficult to apply in complex threat airspace. (2) The second method is based on real-time path planning [9][10][11][12]. With the development of research in this field, many path-planning approaches with significant improvement in timeliness have been proposed, such as artificial potential-field approaches, A Ã algorithm, artificial heuristic approaches and samplingbased path-planning approaches, etc., which can be applied to common path-planning problems in dynamic environments.…”

Section: Introductionmentioning

confidence: 99%

UAV autonomous collision avoidance approach

Wei

Zhang

2017

Automatika

View full text Add to dashboard Cite

The conventional sense-and-avoid collision avoidance mode of UAV (unmaned aerial vehicle) lacks applicability and timeliness in a multi-threat environment. In this paper, a new efficient collision avoidance approach for uncertain threat environments derived from the idea of autonomous mental development is proposed. The proposed collision avoidance pattern consists of a sensory layer, a logic layer and a development layer. The threat information is sensed using the sensory layer, and the path planning approach in the logical layer is applied to the output configuration of UAV. In the development phase, the developmental networks approach is used for online learning, training and updating the logical layer so as to form the sense-action mapping, which is stored as the "basic experience" for UAV executing the avoidance manoeuvre. In the implementation phase, the command is executed by matching the sensing information and action base. The simulation results show that the proposed approach has better timeliness compared to the conventional approaches.

show abstract

Automatic collision avoidance for manually tele-operated unmanned aerial vehicles

Cited by 43 publications

References 36 publications

High speed navigation for quadrotors with limited onboard sensing

High speed navigation for quadrotors with limited onboard sensing

Close visual bridge inspection using a UAV with a passive rotating spherical shell

UAV autonomous collision avoidance approach

Contact Info

Product

Resources

About