Shape-Aware Whole-Body Control for Continuum Robots with Application in Endoluminal Surgical Robotics

This paper presents a shape-aware whole-body control framework for tendon-driven continuum robots with direct application to endoluminal surgical navigation. Endoluminal procedures, such as bronchoscopy, demand precise and safe navigation through tortuous, patient-specific anatomy where conventional tip-only control often leads to wall contact, tissue trauma, or failure to reach distal targets. To address these challenges, our approach combines a physics-informed backbone model with residual learning through an Augmented Neural ODE, enabling accurate shape estimation and efficient Jacobian computation. A sampling-based Model Predictive Path Integral (MPPI) controller leverages this representation to jointly optimize tip tracking, backbone conformance, and obstacle avoidance under actuation constraints. A task manager further enhances adaptability by allowing real-time adjustment of objectives, such as wall clearance or direct advancement, during tele-operation. Extensive simulation studies demonstrate millimeter-level accuracy across diverse scenarios, including trajectory tracking, dynamic obstacle avoidance, and shape-constrained reaching. Real-robot experiments on a bronchoscopy phantom validate the framework, showing improved lumen-following accuracy, reduced wall contacts, and enhanced adaptability compared to joystick-only navigation and existing baselines. These results highlight the potential of the proposed framework to increase safety, reliability, and operator efficiency in minimally invasive endoluminal surgery, with broader applicability to other confined and safety-critical environments.

Stabilization of Bipedal Robot Motion based on Total Momentum

Bipedal robots adapt to the environment of the modern society due to the similarity of movement to humans, and therefore they are a good partner for humans. However, maintaining the stability of these robots during walking/running motion is a challenging issue that, despite the development of new technologies and the advancement of knowledge, does not yet have a satisfactory solution. In most of the proposed methods by researchers, to maintain the stability of walking bipedal robots, it has been tried to ensure the momentary stability of motion by limiting the motion to multiple constraints. Although these methods have good performance in sustaining stability, they leave the robot away from the natural movement of humans, with low efficiency and high energy consumption. Hence, many researchers have turned to the walking techniques that follow a certain motion limit cycle, in which we can consider the overall stability rather than momentary. In this paper, a method is proposed to maintain the stability of the limit cycle against disturbance. For this purpose, the dynamical model of the biped robot is extracted in the space of total momentum variables and, according to the desired step length and speed, the motion limit cycle is designed. Subsequently, a motion stabilizer is proposed based on the idea of length shift, which is a natural human strategy for sustaining the balance in case of impact. The simulations show that this technique has a good performance in maintaining the stability of motion and has similar responses to human response.

Stability Control of Walking Biped Robots based on Total Momentum

Principle Equation of Motion (for walkers) is derived that later results in introducing two piecewise-continuous dynamical systems namely Simplified Walking Model (SWM) and Complete Walking Model (CWM) which both describe the behavior of walker with emphasis on the motion in horizontal plane. By making some realistic assumptions based on human natural walking, a simplified equation of motion named Step-to-Step Equation of Walking is formulated. By imposing repetition condition on this equation, we reach to a significant finding named Simple and Compound Motion Cycles as general solutions of steady walking. Among motion cycles, Simple Forward Motion Cycle represents normal walking pattern. These cycles have marginal stability that in practice cause the motion to diverge exponentially even under slight disturbance. By defining stabilization of walking as guidance of a motion initiated from arbitrary initial states to a desired motion cycle and controlling the motion about it, two major strategies are presented for stability control of the walkers; 1) Continuous altering of Center of Pressure (CoP) within support polygon, and 2) Continual planning of the step length and duration. Using these two strategies and based on Simplified Walking Model (SWM), four methods of stability control named generally as Motion Cycle Stabilizers are proposed and their theoretical aspects are inspected. To consider the strengths and weaknesses of the proposed stabilizers on Complete Model of Walking (CWM), some simulations are performed on a physical model with realistic constraints. to overcome the deficiencies of the Stabilizers, method of Optimal Stability Control is proposed to complete the solution. Simulations show that the proposed approach for stabilization of biped walkers provides us with a more robust solution compared to traditional approaches and maximally guarantee the stability of walkers.