Challenges for Novice Developers in Rough Terrain Rescue Robots: A Survey on Motion Control Systems

Abstract

Several researchers have revealed the huge potentials of rescue robots in disaster zones. In addition to searching for victims, these intelligent machines are also effective in obtaining useful information from the zones. These functions help to optimize the search and rescue missions. However, the fact that rescue robots have to operate in risky and dangerous environments necessitates the need for such machines to have an efficient motion control system, which can help them to operate autonomously or with minimal human control. This paper reviews the use of reliable controllers in enhancing the sensing capabilities of rescue robots. Huge potential of sensorless sensing method in the rescue robots are highlighted. It is shown that the use of sensorless sensing method enables developer to create simple and cheaper robots for various complex situations. Thus, it is imperative to conduct further studies on how to optimize the operations of robots that lack sensors.

Real-time neural control of all-terrain tracked robots with unknown dynamics and network communication delays

“…In this way, intelligent controllers can be a solution to alleviate this kind of problems, in fact fuzzy controllers have been used to deal with control of uncertain nonlinear systems (Aouf et al, 2019;Tong el al., 2020;Pillai & Suthakorn, 2019), however as has been stated in Jiang et al (2016) neural controllers are better suited to deal with complex control task. Then it is important to remark that the use of RHONN to identify the system to be controlled allow us to use any modern control approach to deal with complex control problems as realtime trajectory tracking, this cannot be done with other intelligent controllers like fuzzy systems (Jiang et al, 2016).…”

“…In Jiang et al (2016), it is presented a deep comparative analysis between the two main methodologies of intelligent control: fuzzy and neural based controllers, then in Farias (2018) it is developed the same comparison with an applicability focused to robotics, these two works illustrate the great capability of intelligent controllers to deal with unknown and unstructured environments, fuzzy controllers are mainly recommended for their simplicity to implementation, besides, fuzzy controller allows the user to include known characteristics of the system by a specialist which cannot be done with neural controllers, however, neural controllers are indicated in complex systems or tasks, where the designer has limited information about the system to be controlled. Use of intelligent control for robotics applications has been deeply studied, for example in Aouf et al (2019) and Tong et al (2020) consider implementation of fuzzy controllers for robots, in Pillai & Suthakorn (2019) it is presented a compendium of challenges in motion control of rough terrain rescue robots. In Rios et al (2017), an implementation of the NIOC scheme applied to a modified HD2® (HD2 is a registered trademark of SuperDroid Robots) is presented, such work presents the simulation and experimental results as well as a comparison of the NIOC scheme with a super twisting scheme.…”

Robot Platooning Strategy for Search and Rescue Operations

“…Mitchell [2] includes a review of how SAR robots helped in search and rescue operations in the recent natural disasters that hit North America. SAR robot-based operations have strict constraints on the duration and reliability of the mission assigned to each robot [3]. For saving lives, the SAR robot needs to reach the victims' location as soon as possible.…”