On hybrid modeling and control of a multi-propeller multifunction aerial robot with flying-walking locomotion

Wilderness Search for Lost Persons Using a Multimodal Aerial-Terrestrial Robot Team

Mobile robots that are capable of multiple modes of locomotion may have tangible advantages over unimodal robots in unstructured and non-homogeneous environments due to their ability to better adapt to local conditions. This paper specifically considers the use of a team of multimodal robots capable of switching between aerial and terrestrial modes of locomotion for wilderness search and rescue (WiSAR) scenarios. It presents a novel search planning method that coordinates the members of the robotic team to maximize the probability of locating a mobile target in the wilderness, potentially, last seen on an a priori known trail. It is assumed that the search area expands over time and, thus, an exhaustive search is not feasible. Earlier research on search planning methods for heterogeneous though unimodal search teams have exploited synergies between robots with different locomotive abilities through coordination and/or cooperation. Work on multimodal robots, on the other hand, has primarily focused on their mechanical design and low-level control. In contrast, our recent work, presented herein, has two major components: (i) target-motion prediction in the presence of a priori known trails in the wilderness, and (ii) probability-guided multimodal robot search-trajectory generation. For the former sub-problem, the novelty of our work lies in the formulation and use of 3D probability curves to capture target distributions under the influence of a priori known walking/hiking trails. For the latter, the novelty lies in the use of a tree structure to represent the decisions involved in multimodal probability-curve-guided search planning, which enables trajectory generation and mode selection to be optimized simultaneously, for example, via a Monte Carlo tree search technique. Extensive simulations, some of which are included herein, have shown that multimodal robotic search teams, coordinated via the trajectory planning method proposed in this paper, clearly outperform their unimodal counterparts in terms of search success rates.

Modeling and control of a hexacopter with a passive manipulator for aerial manipulation

In this paper, a multi-propeller aerial robot with a passive manipulator for aerial manipulation is presented. In order to deal with the collision, external disturbance, changing inertia, and underactuated characteristic during the aerial manipulation, an adaptive trajectory linearization control (ATLC) scheme is presented to stabilize the multi-propeller aerial robot during the whole process. The ATLC controller is developed based on trajectory linearization control (TLC) method and model reference adaptive control (MRAC) method. The stability of the proposed system is analyzed by common Lyapunov function. Numerical simulations are carried out to compare the ATLC with TLC controller facing collision, external disturbance and changing inertia during an aerial manipulation. Experimental results prove that the developed robot can achieve aerial manipulation in the outdoor environment.

A Survey on Mechanical Solutions for Hybrid Mobile Robots

This paper presents a survey on mobile robots as systems that can move in different environments with walking, flying and swimming up to solutions that combine those capabilities. The peculiarities of these mobile robots are analyzed with significant examples as references and a specific case study is presented as from the direct experiences of the authors for the robotic platform HeritageBot, in applications within the frame of Cultural Heritage. The hybrid design of mobile robots is explained as integration of different technologies to achieve robotic systems with full mobility.