This paper presents the development and control methodology of a military rescue robot for a casualty extraction task. The new rescue robot (HURCULES) equipped with electric actuators for the casualty extraction task on the battle field is introduced. In this paper, mechanical designs of the HURCULES are described in detail. One of the noticeable features in the mechanical design is to use the worm gear in the joint to maintain the safety of the casualty even with power‐off and to reduce the energy through a selected operating mode. Moreover, unlike the upper body of a conventional humanoid robot, the chest plate is installed and used to properly distribute the casualty’s weight to the dual‐arm manipulator and the chest plate when carrying the wounded person. The HURCULES is valuable because the rescue robots for use on the battle field are very rare. And, the HURCULES is the first rescue robot for use on the battle field in South Korea. Primarily, a semiautonomous control strategy is applied to the HURCULES. The maneuvering stability of the HURCULES is needed when approaching and escaping a casualty while maneuvering on uneven terrain, and it maintains autonomously by the HURCULES. A variety of maneuvering experiments on various terrains were conducted, and satisfactory results for the casualty extraction task were obtained. In particular, the field experiments in this paper were performed at an accredited test site. Besides, additional experiments were conducted to enhance the field applicability.

We present a sampling-based control approach that can generate smooth actions for general nonlinear systems without external smoothing algorithms. Model Predictive Path Integral (MPPI) control has been utilized in numerous robotic applications due to its appealing characteristics to solve nonconvex optimization problems. However, the stochastic nature of sampling-based methods can cause significant chattering in the resulting commands. Chattering becomes more prominent in cases where the environment changes rapidly, possibly even causing the MPPI to diverge. To address this issue, we propose a method that seamlessly combines MPPI with an input-lifting strategy. In addition, we introduce a new action cost to smooth control sequence during trajectory rollouts while preserving the information theoretic interpretation of MPPI, which was derived from non-affine dynamics. We validate our method in two nonlinear control tasks with neural network dynamics: a pendulum swing-up task and a challenging autonomous driving task. The experimental results demonstrate that our method outperforms the MPPI baselines with additionally applied smoothing algorithms.

This paper introduces a new rescue robot consisting of dual-manipulator and variable configuration mobile platform for multi-purpose such as casualty extraction and hazardous goods transport. A specific rescue motion strategy using a whole-body is suggested to tackle characteristics of the robot configuration and balancing issue. In order to take into account safety and stability of the robot during the rescue motions, some restrictions are reflected into redundant domain of the robot with different priority. For stable motion control in various scenarios, a singularityrobust inverse kinematics is adopted and modified to induce smoother robot movement. The robustness of the control approach is checked numerically by comparing other method and experiments for the rescue motion strategy are carried out by using a small-scaled simulator in place of the rescue robot under development.

This paper proposes practical hardware design strategies and control methods for a rescue robot to save patients in disastrous environments. None of the existing humanoid robots have not shown the capability to efficiently execute rescue tasks for transferring a human to a safe place in a highly unstructured world. To resolve this problem a new form of powerful dual arm mechanism and hybrid tracked-legged mobile platform is developed and the motion is synthesized with dynamics based optimization and a modified hierarchical control scheme. These new design and control policies enable us to simultaneously enhance the manipulation performance and driving stability which have been verified through both in extensive numerical simulations and physical experiments where the rescue robot and whole-body control are indeed required.