This paper presents a new contact-motion planning algorithm which searches not only contacts and motions but also contact transition strategies. Especially, this paper focus on slide-type and detach-type switching. Our idea is to separate the planning process into 3 steps: select contact transition strategy, search contact state, and generate motion. This separation prevents from complicating the motion search process which is generally a non-linear optimization process and is computationally expensive, and enables to manually control the priorities of all transition strategies. The contribution of this paper is to develop a new concept of contact-motion planning algorithm involving contact transition strategies switching, and to examine the algorithm's search capabilities through 2 scenarios: bed seating, and standing up. The bed seating experiment is shown not only in the simulation world but also in the real world with real humanoid robot.
We have reported our Network Robot Service Framework for Non-professionals in our previous paper. Software developers and programmers who are non-professionals of robotics can use robot technology easily on this framework. In this paper, we propose a distributed questionnaire service for service robots on this framework. We describe its design policy and define APIs for it to build a distributed questionnaire service system easily. Furthermore, we implement a distributed questionnaire service system as a prototype system, and verify the ease of development. Additionally, through demonstration experiment at a big event using this prototype system, we verify the effectiveness of our proposal. It can be assumed that this service with plural low-price robot can be used by a tourist spot or some community as well as an event.
Since quadruped robots have been considered to be effective on rough terrain, they have been studied in various fields such as rescue and planetary exploration. In the legged locomotion literature, researchers mostly focus on mechatronics hardware and actuation systems of quadruped robots. Nevertheless, such systems may be questionable from the stability point of view, in particular, for dynamic walking and running. Therefore, to develop high locomotion capabilities to adjust to different type of terrains, we propose a new type of compliance control based on reinforcement learning. In this method, compliance control parameters of each joint can be adjusted by external forces acting on the robot feet. Due to this adaptive mechanism, dynamically balanced jumping motion and trotting quadruped locomotion on the rough terrain can be realized. In order to demonstrate the efficiency of the proposed method, jumping and trotting experiments were conducted on our quadruped robot. As a result, we obtained periodic, continuous and repetitive jumping and trotting cycles in which dynamic balance was ensured.