(a)Trial FM-V31.
(b)Trial FM-V33.
(c)Trial FM-V34.
Figure 6.25: Robots’ assumed poses during the sample mission - Coyote III initially at (0,0), SherpaTT remains at (3,0). Target waypoints are numbered according to the resulting se-quence. Note that the orientation of Coyote III does not change, e.g., when moving from way-point 1 to 2, since the robot is driving backwards (see Table6.2).
additional characteristic of the planning approach: the explicit definition of qualitative time-points constraints the solution space, e.g., a mobile agent cannot deviate from its path when it transitions between two locations and no intermediate timepoint exists. In the baseline mis-sion Coyote III can only transport the sampling payload to SherpaTT between t0 and t1, due to the existence of the intermediate timepoint t1.5. This characteristic can be interpreted as a limitation of the current planning approach which results from the use of the temporally expanded network. However, additional preference constraints can also be derived from this observation, e.g., constraints which restrict or permit the deviation from the direct path for a transition between two locations.
The implementation of the planned baseline mission shows, that coalition structure changes vary in time and therefore vary in cost. The implemented autonomous coalition structure change shows only a payload exchange, but it illustrates the complexities of structure changes and their dependence on subsystems. For a cooperative approach two robots have to be op-erational so that a coalition structure change can be performed. However, robot activities can fail and failure handling routines are required for the cooperative approach, so that necessary preconditions for further robot actions can be (re)established. Additionally, coalition structure changes can fail and therefore have also to be accounted for as a risk. The implementation of the sample return mission shows, that a cooperative docking approach will benefit from ad-ditional redundancy. Such redundant design would estimate robot poses from the distributed SLAM as well as by visual means, and fuse this information for a fully cooperative docking approach, where each robot can monitor and support the activity of the other robot.
EMI: a Single Point of Failure TheEMIis the key element of the reconfigurable multi-robot system. But the EMIis also a point of failure and its design is critical for many levels of op-eration. Hence, the design of the EMI has not only to meet physical requirements such as load, data and power throughout. The design must also consider physical and virtual guidance (visibility or detectability) to support automated docking procedures and account for context dependant influences of EMI features during such operations. The last aspect refers to the observation that theEMI’s mechanical guidance pins have been implemented to support the docking process. Under a low positioned sun, they lead to long shadows on the interface which critically influence the visual detection of the interface pose. Therefore, anyEMIdesign that enables a reconfigurable multi-robot system must be critically assessed and validated under conditions of the target environment and after defining acceptance tests. An additional single point of failure is the marker-based, pose-guided visual servoing approach which relies on the bottommost camera attached to the end effector. Hence, a payload item can only be exchanged as long as the bottommost camera is operational. Additional redundancy for the marker-based pose detection can be introduced by the previously mentioned pose estimation. The detection of a robot’s pose in combination with either prior and ad-hoc exchanged information about the relative target interface pose, can serve as basis for an alternative docking approach. This in-formation can also be part of an extended organisation model. As a benefit of reconfigurability, a failing end effector camera can also be compensated for by attaching a payload item.
The validation experiment uses an identical set of markers for all maleEMIs. For scalability, however, each EMI has to be uniquely identifiable, e.g., by using an additional marker for identification. Likewise the organisation model has to be maintained in a distributed way, in order to allow a mapping between interfaces and the corresponding agents.
The EMI design can come with features which limit its applicability, e.g., as shown for the
operation with long shadows. However, a multi-robot system has an increased potential to actively control the operation environment. Lighting conditions can be actively influenced to avoid reflections and shadows, e.g., by either changing the docking approach and the position of each mobile agent or by using collaborative systems to shadow or illuminate designated areas.
Visual Servoing The current design of the visual servoing approach has limitations. Firstly, it depends on a teaching procedure. This procedure will not be necessary when either EMIs (including the augmentation with markers) can be manufactured with sufficient accuracy and precision, or when the marker detection is replaced with a more capable interface detection algorithm. The marker detection acts as a placeholder for any kind of interface and robot de-tection mechanism. Secondly, the current approach does not exploit the rotational invariance of the EMIdesign and uses only a single reference pose. But a full exploitation of the rota-tional invariance requires not only the support through the visual servoing approach. The organisation model has to be embedded into the operational architecture also, so that it re-flects the current state of the organisation and more specifically the exact geometrical state of a composite agent.
Superadditive Functionality Superadditive functionalities of a reconfigurable system can be actively designed, e.g., as shown by the development of extension modules (cf.(Brinkmann, Cordes, et al.2018; Sonsalla, Cordes, L. Christensen, Roehr, et al. 2017b)). As seen with the sampling module, a challenge for the design of the tool exchange lies in the identification and formalisation of usage constraints. The design of the sampling module has been performed without the explicit validation through a higher level sampling routine. So, while the design of reconfigurable (here: immobile) agents can be performed independently from other systems due to the EMI, the example shows that this can lead to severe usage constraints. Hence, a co-development process for those agents which enable a superadditive functionality should be favoured. Furthermore, known geometrical constraints could also be used to characterise agent functionalities further, so that a more sophisticated agent description has to be part of the organisation model. While the active design of superadditive functionality will be the primary focus for most developments, some superadditive functionality can also be discovered as the result of emergence. A detailed geometrical description in the organisation model can also be combined with evolutionary search in order to identify sleeping functionalities.
Generalisation of Coalition Structure Changes Coalition structure changes require detailed action planning for the involved robots. Reusable and parametrisable scene scripts for the co-operative approach of two robots can facilitate the execution of multi-robot missions. Since they form essential building blocks of a reconfigurable multi-robot mission any increase of robustness and speed of performing these scene scripts will lead to a higher success rate of re-configurable multi-robot missions. A generic scene script for a docking approach between two agentsa0and a1is provided with Algorithm1. The algorithms suggests an increased level of active cooperation between the two approaching agents, so that inter-robot communication has to be intensified. The experiment FM-VXX was based on an initially known shared reference frame. A scalable approach builds on robots which are capable to establish a shared reference frame independent of their starting conditions, e.g., by identification and sharing of their rela-tive poses. D. Fox et al. (1999) have shown that accounting for relarela-tive poses also improves the
localisation error compared to the use of a single robot for localisation and is therefore an avail-able means to improve any multi-robot operation. The experiment FM-VXX does not negotiate a docking plan, and uses a predefined action sequence instead. Such sequence will be appli-cable to a limited set of situations, but additional local planning can increase the flexibility of the approach.
Algorithm 1:Pseudo code for a cooperative (two agent) approach.
Data: A← {a0, a1}; // Agent pool
1 a0sends request for cooperation;
2 ifa1does not confirm cooperation requestthen
3 abort
4 a0anda1establish a shared reference frame;
5 repeat
6 a0anda1exchange known robot poses;
7 a0anda1select plan template, actively plan, or negotiate the docking plan;
8 a0anda1parameterise and execute docking plan;
9 untila0anda1agree that target poses have been reached;
10 a0anda1test connection;
11 ifconnection establishedthen
12 a0triggers software reconfiguration to change to composite agent {a0, a1};
13 else
14 a0anda1negotiate and initiate local repair routine;
Subsystem Reliability Experiment FM-V33 has demonstrated the single successful perfor-mance of a sample return sequence, and thereby shows the principal feasibility of such ap-proach. However, the success rate is currently 25 percent. A resilient reconfiguration approach requires further improvements regarding error recovery. The reconfigurable multi-robot sys-tem used for FM-V33 has multiple subsyssys-tems which enable the operation of the multi-robot system. The experiment also stresses the importance of each subsystem for the full perfor-mance, or rather the dependence of the performance upon operative subsystems. As long as autonomous failure handling routines are unavailable, a human interaction can be requested as final backup. Trial FM-V34 demonstrates how the online correction of alignment error by a human can turn a failing mission into a success. The overall execution of the mission was not halted or interrupted in FM-V34 and Coyote III’s pose errors have been manually corrected.
After correction Coyote III was positioned within the required workspace(s) and fulfilled the preconditions for subsequent activities, e.g., allowing to align the end effector. Hence, although FM-V34 could not show a fully autonomous performance, it illustrated a feasible failure han-dling strategy: agents pause the cooperative approach upon failure and request human inter-action, a human operator analyses the situation and corrects the last activity, agents continue with the cooperative approach.
Comparison with Previous Approaches The illustrated experiments are the achievements of operating a reconfigurable multi-robot system with respect to the successive development over different projects. In the following, the experiments are compared to the approaches and
results of the related projects LUNARES (Roehr, Cordes, F. Kirchner, and Ahrns 2010) and RIMRES (Roehr, Cordes, and F. Kirchner2014).
In LUNARES a mobile, eight-legged scout robot was commanded from a wheeled rover to perform a mechanical docking procedure. The scout was equipped with a set of markers to enable the pose detection of the system from the wheeled rover. The scout itself was not able to verify its correct positioning, but had to enter the field of vision of the rover’s camera as precondition of the approach. The final pose error remained relatively high with 9 mm is x-direction, 4 mm in y-x-direction, 12 mm in z-direction and a yaw error of 0.7◦. To fulfil the preconditions for docking of a male and a femaleEMIs, we developed in RIMRES an approach between the six-legged scout CREX and the rover Sherpa. In this approach the master (Sherpa) does not move during the final approach, but only the slave (CREX). In RIMRES a higher precision and accuracy of the approach was achieved compared to LUNARES. However, the approach in RIMRES took significantly longer compared to the alignment procedure in the previous section, e.g., an alignment from a random yet visible position in the workspace took 161.72±80.69 seconds.
The use of the manipulator for docking as shown in this thesis shows fast convergence and operates with a higher precision - which is likely the result of an optimisation of the marker layout and a better accuracy of the manipulator compared to the locomotion system of CREX.
Still, all efforts presented in the previous section and in the referred publications are comple-mentary. They show a set of feasible docking approaches which can be used by reconfigurable multi-robot systems.