Commercial Space Transportation and Approaches to landing sites over Maritime Areas

The use of RPAS for coastguard operations rather than manned aircraft introduces several challenges, which will be addressed in this presentation. Typically the envisioned coastguard tasks involve low level flights Beyond Visual Line Of Sight (BVLOS). This requires the Remotely Piloted Aircraft to be equipped with appropriate sensors and on-board Detect and Avoid (DAA) capabilities. We will present a demonstration flight for the project AIRICA (ATM Innovative RPAS Integration for Coastguard Applications), where the detection and separation will be based on active Mode S interrogation and received ADS-B signals. A Detect & Avoid (DAA) system, AirScout, will be implemented and tested. While operating the RPAS on a mission, different airspace environments will be encountered. ATM involvement is crucial, because of the envisaged take-off and landing at local airfields and the involvement of other (manned) aircraft in the mission. The proposed AIRICA flight will include demonstration of the RPAS under ATC and demonstration of the DAA function with planned intruder aircraft (manned). To prepare the demonstration flights, a real-time man-in-the-loop simulation environment has been set-up, where real air traffic controllers, a real pilot (for other traffic), and a pilot at an RPAS ground control station (GCS) participated to evaluate the concept. The simulations paved the way for real flight demonstrations with a MALE (Medium Altitude Long Endurance) RPAS in non-segregated airspace for maritime surveillance missions

www.cs.uu.nl Useful Cycles in Probabilistic Roadmap Graphs

Over the last decade, the probabilistic road map method (prm) has become one of the dominant motion planning techniques. Due to its random nature, the resulting paths tend to be much longer than the optimal path despite the development of numerous smoothing techniques. Also, the path length varies a lot every time the algorithm is executed. In this paper we present a new technique that results in higher quality (shorter) paths with much less variation between the executions. The technique is based on adding useful cycles to the roadmap graph.

Motion Planning for Camera Movements in Virtual Environments

When users navigate through a virtual environment they often directly control the camera. Such direct control is di#cult for inexperienced users and results in rather ugly camera motions that easily lead to motion sickness. In this paper we describe a new technique for automatic generation of camera motion using motion planning techniques from robotics. In this approach the user simply specifies a required goal position (and orientation) using e.g. a map, and the system automatically computes a smooth camera motion from the current position and orientation to the required position (and orientation). As preprocessing the approach uses the probabilistic roadmap method to compute a roadmap through the environment. When a camera motion is required a path is obtained from the roadmap which is then improved by various smoothing techniques to satisfy camera constraints

An effective framework for path planning amidst movable obstacles

This paper addresses the problem of navigating an autonomous moving entity in an environment with both stationary and movable obstacles. If a movable obstacle blocks the path of the entity attempting to reach its goal configuration, the entity is allowed to alter the placement of the obstacle by manipulation (e.g. pushing or pulling), to clear its path. This paper presents a probabilistically complete framework for solving path planning problems among movable obstacles. Heuristics are presented to provide efficient solutions for problems in environments encountered in practical situations.

Innovative RPAS Airspace Integration for Coastguard Missions

The use of RPAS for coastguard operations rather than manned aircraft introduces several challenges, which will be addressed in this presentation. Typically the envisioned coastguard tasks involve low level flights Beyond Visual Line Of Sight (BVLOS). This requires the Remotely Piloted Aircraft to be equipped with appropriate sensors and on-board Detect and Avoid (DAA) capabilities. We will present a demonstration flight for the project AIRICA (ATM Innovative RPAS Integration for Coastguard Applications), where the detection and separation will be based on active Mode S interrogation and received ADS-B signals. A Detect & Avoid (DAA) system, AirScout, will be implemented and tested. While operating the RPAS on a mission, different airspace environments will be encountered. ATM involvement is crucial, because of the envisaged take-off and landing at local airfields and the involvement of other (manned) aircraft in the mission. The proposed AIRICA flight will include demonstration of the RPAS under ATC and demonstration of the DAA function with planned intruder aircraft (manned). To prepare the demonstration flights, a real-time man-in-the-loop simulation environment has been set-up, where real air traffic controllers, a real pilot (for other traffic), and a pilot at an RPAS ground control station (GCS) participated to evaluate the concept. The simulations paved the way for real flight demonstrations with a MALE (Medium Altitude Long Endurance) RPAS in non-segregated airspace for maritime surveillance missions

Path Planning in Changeable Environments

(met een samenvatting in het Nederlands

Path Planning for Pushing a Disk using Compliance

We consider the path planning problem for a robot that pushes a disk shaped object in an environment among obstacles. Instead of only allowing the object to move through the free space, we also allow the object to slide along the boundaries of the environment using compliance extending the possibilities for the robot to find a push path. We present an exact algorithm that, given a path for the object consisting of k sections, preprocesses the environment consisting of n non-intersecting line segments in O(n² log n) and reports a push path in O(knlog n) time or reports failure if no path exists. Under the weak assumption of low obstacle density, the query time is reduced to O((k + n) log n)