17 accepted papers
Collision-free planning is essential for bipedal robots operating within unstructured environments. This paper presents a real-time Model Predictive Control (MPC) frame-work that addresses both body and foot avoidance for dynamic bipedal robots. Our contribution is two-fold: we introduce (1) a novel
Open-loop stable limit cycles are foundational to legged robotics, providing inherent self-stabilization that minimizes the need for computationally intensive feedback-based gait correction. While previous methods have primarily targeted specific robotic models, this paper introduces a general frame
For effective operation in challenging outdoor environments, mobile unmanned robots face stiff and competing demands including payload capacity, driving speed, range, as well as the ability to traverse rough terrain. To address these issues we introduce the hybrid wheel-leg quadrupedal robot WaLTER.
Robots routinely encounter obstacles and rough terrain, but terrain curvature is seldom included in models for real-time algorithms. We present a closed-form dynamic model for rolling with two planar smooth curves, and apply it to sagittal-plane locomotion problems. We assumed that the body rolls wi…
The human world is full of risks that threaten failure of robotic tasks. Dynamic robots, such as agile drones and walking bipeds, are particularly susceptible to failure because their time to make critical decisions is short. This work seeks a control algorithm which adapts to failures and repriorit…
In real-world settings, bipedal robots must avoid collisions with people and their environment. Further, a biped can choose between modes of avoidance: (1) adjust its pose while standing or (2) step to gain maneuverability. We present a real-time motion planner and multibody control framework for dy…
We present a real-time motion planner that avoids multiple moving obstacles without knowing their dynamics or intentions. This method uses convex optimization to generate trajectories for linear plant models over a planning horizon (i.e. model-predictive control). While convex optimizations allow fo…
We want robots to complete assigned tasks even when unexpected task pressures arise, either from the robot or the environment. This paper presents a method of both learning sources of task failure in situ and rapidly planning new motions on-the-fly to accommodate them. This “risk-adaptive” approach…
Tracks, wheels, and legs are all useful locomotion modes for Unmanned Ground Vehicles (UGVs), and ground robots that combine these mechanisms have the potential to climb over large obstacles. As robot morphologies include more degrees of freedom and obstacles become increasingly large and complex, U…
Heterogeneous robotic systems in the field often encounter bodies of water with unknown traversability properties. One approach to measuring depth, current, soil composition, etc. is via an in situ underwater sensor being dragged by cable attached to a maneuvering airborne multicopter - which entail…
As we build our legged robots smaller and cheaper, stable and agile control without expensive inertial sensors becomes increasingly important. We seek to enable versatile dynamic behaviors on robots with limited modes of state feedback, specifically proprioceptive-only sensing. This work uses model-…
Out in the field, bipedal robots need to travel on terrain that is uneven, non-rigid, and sometimes moving beneath their feet. We present a force-based double support balancing controller for such dynamic terrain scenarios for bipedal robots, and test it on the robotic bipedal platform "Tallahassee…
This paper describes the design, control and initial experimental results of the quadruped robot LLAMA. Designed to operate in a human-scale world, this 67kg-class, all-electric robot is capable of rapid motion over a variety of terrains. Thanks to a unique leg configuration and custom high-torque,…
Robots encounter many risks that threaten the success of practical locomotion tasks. Legs break, electrical components overheat, and feet can unexpectedly slip. When all risks cannot be completely avoided, how does a robot decide its best action? We present a method for planning robot motions by rea…
Transient locomotion is still poorly understood in terms of planning and implementation on robotic platforms, with most research concentrated on steady-state motion. In this letter, we investigate optimal rapid acceleration (positive and negative) maneuvers of a planar numerical quadruped and biped
Practical use of robots in diverse domains requires programming for, or adapting to, each domain and its unique characteristics. Failure to do so compromises the ability of the robot to achieve task-relevant objectives. Here we describe how the learned terrain reaction force profiles of a hopping ro…
We investigate the task-optimality of legged limit cycles and present numerical evidence supporting a simple general locomotion-planning template. Limit cycles have been foundational to the control and analysis of legged systems, but as robots move toward completing real-world tasks, are limit cycle…