This two-part paper discusses the analysis and control of legged locomotion in terms of N-step capturability: the ability of a legged system to come to a stop without falling by taking N or fewer steps. We consider this ability to be crucial to legged locomotion and a useful, yet not overly restrictive criterion for stability. In this part (Part 1), we introduce a theoretical framework for assessing N-step capturability. This framework is used to analyze three simple models of legged locomotion. All three models are based on the 3D Linear Inverted Pendulum Model. The first model relies solely on a point foot step location to maintain balance, the second model adds a finite-sized foot, and the third model enables the use of centroidal angular momentum by adding a reaction mass. We analyze how these mechanisms influence N-step capturability, for any N > 0. Part 2 will show that these results can be used to control a humanoid robot.

This two-part paper discusses the analysis and control of legged locomotion in terms of N-step capturability: the ability of a legged system to come to a stop without falling by taking N or fewer steps. We consider this ability to be crucial to legged locomotion and a useful, yet not overly restrictive criterion for stability. Part 1 introduced the N-step capturability framework and showed how to obtain capture regions and control sequences for simplified gait models. In Part 2, we describe an algorithm that uses these results as approximations to control a humanoid robot. The main contributions of this part are (1) step location adjustment using the 1-step capture region, (2) novel instantaneous capture point control strategies, and 3) an experimental evaluation of the 1-step capturability margin. The presented algorithm was tested using M2V2, a 3D force-controlled bipedal robot with 12 actuated degrees of freedom in the legs, both in simulation and in physical experiments. The physical robot was able to recover from forward and sideways pushes of up to 21 Ns while balancing on one leg and stepping to regain balance. The simulated robot was able to recover from sideways pushes of up to 15 Ns while walking, and walked across randomly placed stepping stones.

This paper presents a momentum-based control framework for floating-base robots and its application to the humanoid robot “Atlas”. At the heart of the control framework lies a quadratic program that reconciles motion tasks expressed as constraints on the joint acceleration vector with the limitations due to unilateral ground contact and force-limited grasping. We elaborate on necessary adaptations required to move from simulation to real hardware and present results for walking across rough terrain, basic manipulation, and multi-contact balancing on sloped surfaces (the latter in simulation only). The presented control framework was used to secure second place in both the DARPA Robotics Challenge Trials in December 2013 and the Finals in June 2015.

This article is a summary of the experiences of the Florida Institute for Human & Machine Cognition (IHMC) team during the DARPA Robotics Challenge (DRC) Trials. The primary goal of the DRC is to develop robots capable of assisting humans in responding to natural and manmade disasters. The robots are expected to use standard tools and equipment to accomplish the mission. The DRC Trials consisted of eight different challenges that tested robot mobility, manipulation, and control under degraded communications and time constraints. Team IHMC competed using the Atlas humanoid robot made by Boston Dynamics. We competed against 16 international teams and placed second in the competition. This article discusses the challenges we faced in transitioning from simulation to hardware. It also discusses the lessons learned both during the competition and in the months of preparation leading up to it. The lessons address the value of reliable hardware and solid software practices. They also cover effective approaches to bipedal walking and designing for human‐robot teamwork. Lastly, the lessons present a philosophical discussion about choices related to designing robotic systems.

The concept of 'Limit Cycle Walking' in bipedal robots removes the constraint of dynamic balance at every instance during gait. We hypothesize that this is crucial for the development of increasingly versatile and energy-effective humanoid robots. It allows the application of a wide range of gaits and it allows a robot to utilize its natural dynamics in order to reduce energy use. This paper presents the design and experimental results of our latest walking robot 'Flame' and the design of our next robot in line 'TUlip'. The focus is on the mechanical implementation of series elastic actuation, which is ideal for Limit Cycle Walkers since it offers high controllability without having the actuator dominating the system dynamics. Walking experiments show the potential of our robots, showing good walking performance, though using simple control.