commands exchanged between the master and slave. For example if the slave robot receives a single type of command and the master side receive only one type of feed- back, the architecture is named 2-channel bilateral tele-operation. In [Son–2013] the human operator’s performances, in terms of maneuverability and perceptual sensitivity, through bilateral tele-operation for multiple robots are investigated. In particular, force cues are used to transcribe the proximity of obstacles in the remote environment and velocity cues to transcribe the velocity mismatch of the robots.
Based on the type of commands accepted by the slave robots and the kind of commands accepted by the master, impedance and admittance framework are used. All combination of commands type for the master and slave side are possible and there is no a priori best choice, combination shall be tested and evaluated based on robustness (w.r.t. communication, model uncertainty, external disturbances, ...), task performance, tele-presence (as felt by the operator) and transparency (dynamic cancellation of master and slave systems). Evaluation of the impact of different haptic cues on UAV operators can be found in [Son–2013]. Comparison of transparency as defined by control theory and felt by user is investigated in [Hirche– 2012].
There are two additional ways of using tele-operation from and high level control perspective. Haptic cues can be used to render virtual fixtures or virtual fences to the operator, the former helping guiding some task relevant motions and the later shielding some area of the environment, e.g., to avoid collision. Also the tele-operation can be used in a shared control paradigm, where the slave system autonomously carries out a task, and the master is used to generate local trajectory modifications. Either spatial, i.e., altering the trajectory to avoid and obstacle, or temporal, i.e., slowing down the motion to reduce dynamical efforts. These two kind of modifications allow the operator to provide update on the system or the environment without triggering re-planning.
2.5 Collaborative Aerial Physical Interaction
From a semantic stand point, collaboration (working jointly with other toward a common goal) and cooperation (operating together to realize a task) are considered equivalent. A collaboration denotes a joint work, it does not necessary involve physical interaction, with the environment or with the other collaborators, that is to say heterogeneous robots, ground and AV, mapping/monitoring an area is a collaboration task but not relevant in the scope of APhI.
Collaboration between Aerial Vehicles
A few works considering swarm, or team of AR, performing APhI with the environ- ment or inside the swarm have been presented, see Fig. 2.8. Most notably, swarm of AR are used for collaborative construction, as in [Augugliaro–2014], to build a tower structure out of bricks or to build tensile structures, e.g., bridge, as in [Augugliaro– 2015], or to assemble cubic structure in [Lindsey–2011] or more complex structure
(a) [Lindsey–2011] (b) [Bernard–2011] (c) [Augugliaro–2013]
Figure 2.8 – Aerial Robot collaborations, (a) collaborative structure assembly by a team of ARs, (b) collaborative load transportation via tether and (c) human-AR collaboration for assembly tasks.
with a dedicated construction planning in [Sempere–2014] [MunozMorera–2015]. In this case the physical interaction is not affected by the other members of the swarm. Or in the well developed case of cooperative load transportation, by team of AR. This results in a group of AR tasked to transport a load in a coordinated fashion, the loading being a bar directly grasped [Kim–2017](and previous) or at- tached by cables [Gassner–2017] or some structure [Wu–2014][Michael–2009]. One can also mention the work presented in [Nguyen–2015] where three quadrotors are attached to a rigid structure via passive rotational joints, the task is to coordinate the structure motion to use a tool attached to the structure. Another interesting work is presented in [Ritz–2012], where three quadrotors are attached to a net by mean of rope and they trow and catch balls with the net, the trowing is particularly interesting in the scope of collaborative physical interaction.
Collaboration with Ground Vehicles
An exciting topic in APhI, is the interaction with ground robot in order to allevi- ate some drawbacks of AR, e.g., the autonomy/payload. The work going in that direction mostly showcase simulation results. In [Tognon–2016a] and [Papachristos– 2014b] a cable is taut between the ground vehicle and the AV, this can be a solution to enhance power endurance of the MAV. The former focus on the trajectory control of the MAV, while the latest in focused on the autonomous navigation and map- ping. Some autonomous landing on moving robot as been demonstrated outdoor in [Vlantis–2015]. Other occurrences of Aerial-Ground cooperation can be found in [Spica–2012] and [Gawel–2017], where an AR picks-up a object from a moving ground robot and in [Nguyen–2016] where the foundations for associating a ground mobile vehicle and an AV to transport an object are sketched.
2.5. Collaborative Aerial Physical Interaction 25 Collaboration with Human
Despite the vast literature on human-robot collaborative tasks, it seems that few works in the direction of physical collaboration between human and AR have been presented so far in a conclusive way. Choice has been made not to consider collision detection and recovery as a cooperative interaction, as it is not collaborative. A work in the collaborative direction can be found in [Mueller–2011], AV juggling balls with human or other AV. In [Augugliaro–2013] a human-robot physical interaction is tested, relying on admittance control scheme, see Fig. 2.8c.
In a recent work [Rajappa–2017] a framework and MAV for human-UAV interac- tions are presented and lay the foundation of possible safe human-UAV cooperation. Another framework for human-UAV safe interaction is presented in [Tomić–2014] and relies on impedance control. The safe interaction control is a first step toward collaboration between human and AR.
Part II
MAGMaS: Aerial-Ground
Co-manipulation
Chapter 3
MAGMaS: Aerial-Ground Co-manipulation
Motivations and Modeling
Contents3.1 Motivations . . . 29