Walking on compliant terrain presents a substantial challenge for individuals with lower-limb amputation, further elevating their already high risk of falling. While powered ankle-foot prostheses have demonstrated adaptability across speeds and rigid terrains, control strategies optimized for soft or compliant surfaces remain underexplored. This work experimentally validates an admittance-based control strategy that dynamically adjusts the quasi-stiffness of powered prostheses to enhance gait stability on compliant ground. Human subject experiments were conducted with three healthy individuals walking on two bilaterally compliant surfaces with ground stiffness values of 63 and 25 kN/m, representative of real-world soft environments. Controller performance was quantified using phase portraits and two walking stability metrics, offering a direct assessment of fall risk. Compared to a standard phase-variable controller developed for rigid terrain, the proposed admittance controller consistently improved gait stability across all compliant conditions. These results demonstrate the potential of adaptive, stability-aware prosthesis control to reduce fall risk in real-world environments and advance the robustness of human-prosthesis interaction in rehabilitation robotics.

In this paper, we present an energy-conservation based control architecture for stable dynamic motion in quadruped robots. We model the robot as a Spring-loaded Inverted Pendulum (SLIP), a model well-suited to represent the bouncing motion characteristic of running gaits observed in various biological quadrupeds and bio-inspired robotic systems. The model permits leg-orientation control during flight and leg-length control during stance, a design choice inspired by natural quadruped behaviors and prevalent in robotic quadruped systems. Our control algorithm uses the reduced-order SLIP dynamics of the quadruped to track a stable parabolic spline during stance, which is calculated using the principle of energy conservation. Through simulations based on the design specifications of an actual quadruped robot, Ghost Robotics Minitaur, we demonstrate that our control algorithm generates stable bouncing gaits. Additionally, we illustrate the robustness of our controller by showcasing its ability to maintain stable bouncing even when faced with up to a 10% error in sensor measurements.

Energy efficiency is a critical factor in the performance and autonomy of quadrupedal robots. While previous research has focused on mechanical design and actuation improvements, the impact of gait parameters on energetics has been less explored. In this paper, we hypothesize that gait parameters, specifically duty factor, phase shift, and stride duration, are key determinants of energy consumption in quadrupedal locomotion. To test this hypothesis, we modeled the Unitree A1 quadrupedal robot and developed a locomotion controller capable of independently adjusting these gait parameters. Simulations of bounding gaits were conducted in Gazebo across a range of gait parameters at three different speeds: low, medium, and high. Experimental tests were also performed to validate the simulation results. The findings demonstrate that optimizing gait parameters can lead to significant reductions in energy consumption, enhancing the overall efficiency of quadrupedal locomotion. This work contributes to the advancement of energy-efficient control strategies for legged robots, offering insights directly applicable to commercially available platforms.

Faced with complex and unstructured construction environments, wheeled and tracked robots exhibit significant limitations in terrain adaptability and flexibility, making it difficult to meet the requirements of autonomous operation. Inspired by ants in nature, this paper proposes a leg configuration design and optimization method tailored for construction scenarios, aiming to enhance the autonomous mobility of construction robots. This paper analyzes the full operational motion performance of the leg during both swing and stance phases. First, based on kinematic modeling and multi-dimensional workspace analysis, the concept of an "improved workspace" is introduced, and graphical methods are used to optimize the leg dimensions during the swing phase. Furthermore, a new concept of "average manipulability" is introduced based on the velocity Jacobian matrix, and numerical solutions are applied to obtain the leg segment ratio that maximizes manipulability. To overcome the difficulties associated with traditional analytical methods, virtual prototype simulations are conducted in ADAMS to explore the relationship between the robot body's optimal flexibility and leg segment proportions. In summary, the leg segment proportions with the best comprehensive motion performance are obtained. This study presents the first multi-dimensional quantitative evaluation framework for leg motion performance tailored for construction environments, providing a structural design foundation for legged construction robots to achieve autonomous mobility in complex terrains.

This work presents the design, build, control, and preliminary user data of a locomotion interface called ForceBot. It delivers lower-body haptic interaction in virtual reality (VR), enabling users to walk in VR while interacting with various simulated terrains. It utilizes two planar gantries to give each foot two degrees of freedom and passive heel-lifting motion. The design used motion capture data with dynamic simulation for ergonomic human-robot workspace and hardware selection. Its system framework uses open-source robotic software and pairs with a custom-built power delivery system that offers EtherCAT communication with a 1,000 Hz soft real-time computation rate. This system features an admittance controller to regulate physical human-robot interaction (pHRI) alongside a walking algorithm to generate walking motion and simulate virtual terrains. The system's performance is explored through three measurements that evaluate the relationship between user input force and output pHRI motion. Overall, this platform presents a unique approach by utilizing planar gantries to realize VR terrain interaction with an extensive workspace, reasonably compact footprint, and preliminary user data.

Abstract--Traversing rough terrain requires dynamic bipeds to stabilize themselves through foot placement without stepping in unsafe areas. Planning these footsteps online is challenging given non-convexity of the safe terrain, and imperfect perception and state estimation. First, we develop model-predictive footstep control (MPFC), a single mixed-integer quadratic program which assumes a convex polygon terrain decomposition to optimize over discrete foothold choice, footstep position, ankle torque, template dynamics, and footstep timing at over 100 Hz. We then propose a novel approach for generating convex polygon terrain decompositions online. Our perception stack decouples safe-terrain classification from fitting planar polygons, generating a temporally consistent terrain segmentation in real time using a single CPU thread. We demonstrate the performance of our perception and control stack through outdoor experiments with the underactuated biped Cassie, achieving state of the art perceptive bipedal walking on discontinuous terrain. Figure 1: The bipedal robot Cassie walks up and down brick I. However, dynamic bipedal walking over rough terrain remains challenging for today's perception and control algorithms. This is a highly over the discrete choice of stepping surface and the robot's coupled problem where online terrain estimation is used to dynamics in real time Despite the existence and its precursor [9] represent the first deployment of such a of mature techniques for both underactuated walking, and footstep controller on hardware.

In biomechanics and robotics, elasticity plays a crucial role in enhancing locomotion efficiency and stability. Traditional approaches in legged robots often employ series elastic actuators (SEA) with discrete rigid components, which, while effective, add weight and complexity. This paper presents an innovative alternative by integrating continuously compliant structures into the lower legs of a bipedal robot, fundamentally transforming the SEA concept. Our approach replaces traditional rigid segments with lightweight, deformable materials, reducing overall mass and simplifying the actuation design. This novel design introduces unique challenges in modeling, sensing, and control, due to the infinite dimensionality of continuously compliant elements. We address these challenges through effective approximations and control strategies. The paper details the design and modeling of the compliant leg structure, presents low-level force and kinematics controllers, and introduces a high-level posture controller with a gait scheduler. Experimental results demonstrate successful bipedal walking using this new design.

Powered ankle-foot prostheses can often reduce the energy cost of walking by assisting with push-off. However, focus on providing mechanical work may lead to ignoring or exacerbating common issues with chronic pain, irritation, pressure ulcer development, and eventual osteoarthritis in persons with amputation. This paper presents the design and validation of a novel transtibial prosthesis informed by predictive biomechanical simulations of gait which minimize a combination of user effort and interaction loading from the prosthesis socket. From these findings, the device was designed with a non-biomimetic anterior-posterior translation degree of freedom with a 10 cm range of motion which is primarily position-controlled to change the alignment of the prosthetic foot with the residual limb. The system is both mobile and tethered, with the batteries, actuators, and majority of electronics located in a small backpack. Mechanical loads are transmitted through cables to the prosthesis, minimizing the distal mass carriage required. We measured torque and force sensing accuracy, open loop actuator performance, closed loop torque and position control bandwidth, and torque and position tracking error during walking. The system is capable of producing up to 160 N-m of plantarflexion torque and 394 N of AP translation force with a closed loop control bandwidth of about 7 Hz in both degrees of freedom. Torque tracking during walking was accurate within about 10 N-m but position tracking was substantially affected by phase lag, possibly due to cable slack in the bidirectional mechanism. The prototype was capable of replicating our simulated prosthesis dynamics during gait and offers useful insights into the advantages and the practical considerations of using predictive biomechanical simulation as a design tool for wearable robots.

In this paper, we focus on the kangaroo, which has powerful legs capable of jumping and a soft and strong tail. To incorporate these unique structure into a robot for utilization, we propose a design method that takes into account both the feasibility as a robot and the kangaroo-mimetic structure. Based on the kangaroo's musculoskeletal structure, we determine the structure of the robot that enables it to jump by analyzing the muscle arrangement and prior verification in simulation. Also, to realize a tail capable of body support, we use an articulated, elastic structure as a tail. In order to achieve both softness and high power output, the robot is driven by a direct-drive, high-power wire-winding mechanism, and weight of legs and the tail is reduced by placing motors in the torso. The developed kangaroo robot can jump with its hind legs, moving its tail, and supporting its body using its hind legs and tail.

Miniature-legged robots are constrained by their onboard computation and control, thus motivating the need for simple, first-principles-based geometric models that connect \emph{periodic actuation or gaits} (a universal robot control paradigm) to the induced average locomotion. In this paper, we develop a \emph{modulable two-beat gait design framework} for sprawled planar quadrupedal systems under the no-slip using tools from geometric mechanics. We reduce standard two-beat gaits into unique subgaits in mutually exclusive shape subspaces. Subgaits are characterized by a locomotive stance phase when limbs are in ground contact and a non-locomotive, instantaneous swing phase where the limbs are reset without contact. During the stance phase, the contacting limbs form a four-bar mechanism. To analyze the ensuing locomotion, we develop the following tools: (a) a vector field to generate nonslip actuation, (b) the kinematics of a four-bar mechanism as a local connection, and (c) stratified panels that combine the kinematics and constrained actuation to encode the net change in the system's position generated by a stance-swing subgait cycle. Decoupled subgaits are then designed independently using flows on the shape-change basis and are combined with appropriate phasing to produce a two-beat gait. Further, we introduce ``scaling" and ``sliding" control inputs to continuously modulate the global trajectories of the quadrupedal system in gait time through which we demonstrate cycle-average speed, direction, and steering control using the control inputs. Thus, this framework has the potential to create uncomplicated open-loop gait plans or gain schedules for robots with limited resources, bringing them closer to achieving autonomous control.