Human – Centered Robot Navigation – Towards a Harmoniously Human – Robot Coexisting Environment

Chi-Pang Lam, Chen-Tun Chou, Kuo

IEEE Transaction on Robotics, Vol. 27, No.1, February 2011

Summary

                  Harmonious coexistence of robots with humans is an in interest for improving HRI and the navigation of robots in human environments is rarely studies. Two are the main issue to be addressed: the robot should be able to move autonomously and safely in a human – robot environment in order to complete a specific task and the robot should behave in both human and robot friendly manner during operations, this last issue is the one covered in the authors research. In the literature there are different proposed solutions as traffic rules (which would require to regulate humans’ behavior, which of course is not possible), artificial potential fields (which risk to stuck in local minima), nearness diagram (ND) navigation (which is a reactive navigation approach based on laser scanner), people tracking and so on. The authors propose a human-centered sensitive navigation (HCSN), imposing 6 harmonious rules for human and robot coexistence in the same environment: 1) Collision-free rule; 2) Interference-free rule; 3) Waiting rule; 4) Priority rule; 5) Intrusion rule; 6) Human rule (human have the highest priority). Robots may then have there own internal rules. Also 6 sensitive field have to be defined. The Human Sensitive Field is around the human and assumes an egg shape, bing longer ahead of the human (elliptic) and shorter behind (circle) since it must consider human motion, this field has the highest priority. The Stationary Robot Working Field is the robot working (or just waiting) in a fixed location and has the scape of a disc, it is second in the priority rule. The Movable Robot Working Field is the robot working while moving, it is third in the priority rule and also has a donut shape. The Robot Normal Field is the idle o not working robot, it presents a disc shape and has lowest priority. The Human-Robot Stationary Joint Field present both human and robot working together in stationary position, it assumes a circle shape with the center in the middle between the human and robot. The Human-Robot Moving Joint field also assumes an egg shape (whit longest axis facing the operator). The two combination fields assume the same priority as the Human Sensitive Field, for simplicity the 6 states are denominated as follow in the same order: H1, R1, R2, R3, HR1, HR2. The HCSN design consist of a VLH (Virtual Laser Histogram) which collects all the virtual distance data within 5 meters, this information is used for sensitive-field sensing, while situation identification, together with sensitive field sensed information inputs the motion planner, which then inputs the controller, providing in the end a final output.

Unluckily humans are not easy to localize and paradoxically information regarding them is much less than the ones regarding robots. The motion planner involved the use of ND navigation to fin out a suitable free walking area, while the potential field approach is later used to establish different potential field near the walking area we choose. Different cases are presented, it must be noted that in the priority rule, highest priority may not necessary be assigned to the closed to obstacle, but there is a risk factor applied in order to under preview future closest obstacles, in order to ensure smooth motion.

The priority rule is then used in the calculation of the potential field, which its negative gradient is taken to define the attractive force. Similar computation are then obtained for repulsive force and for repulsive force associated with the soft field (which is the flexible field regarding R2 and R3). The overall force is then the sum of the three and this will determine the sub-goal position, with a matter of a D₀ factor which is a look-ahead distance which is kept smaller into the sensitive field, while the gain is kept smaller for more effective look ahead distance.

Key Concepts

Navigation, Human-Robot Cooperation, Human-Robot Interaction

Key Results

The method, although being complex, can be performed smoothly in real-time environments.

The Dexterous Workspace of Simple Manipulators

Zone-Chang Lai and Chia-Hsiang Meng

IEEE Journal of Robotics and Automation, Vol.4, No.1, February 1988

Summary

                  Many investigation have been one on the determination of extreme position of the end-effector of a manipulator, this paper is regarding instead studies on dexterous workspace with 6 joints axes, which results not been investigated due to complexity in computations.

A dexterous space is defined as a space in which a manipulator’s hand can rotate fully about al axes through any point.

In the manipulator’s workspace, the sphere, called “service sphere” ( SS(P)) , is constructed around a point P with the hand size of the manipulator as a the radius. When the manipulator’s hand reached pint P, then the position of its six joint (J₆) must be located on the sphere. The so called “service point” is the point on the sphere SS(P) which allows to access the position point P. The region containing more service point is called “service region”, if the manipulator can freely move in the region while keeping its hand in contact with P, then this point is defined as “free service region”.

O₄(H) is defined as the set of hand orientations with joints 4 to 6 able to rotate freely, so no boundary exists for a free service region corresponding to appoint in the dexterous workspace. It has been proven that the boundary of a free service region is described by either the boundary of W₁(4), which is the reachable space of joint 4 when joint from 1 to 3 are free to rotate, or the boundary of O₄(H).

In a dexterous space, the robot’s wrist should be capable of generating a full range of orientations, defining what is called “dexterous wrist”, so that when J₆ is at the boundary of a free service region, J₄ is at that boundary of W₁(4), so that it could be considered that the boundary of dexterous workspace is governed by the boundary of W₁(4).

Before performing computation hypothesis for the problem must be checked: it must be check is the robot’s wrist is dexterous, the condition that J₄ is not at the boundary of W₁(4) for all hand orientation must be determined. If a wrist has unlimited revolute joints and its twist angle of joints 4 an 5 equal ±90°, then conditions for the wrist being dexterous are verified.

The boundary of W₁(4) can be described or by rotational limits of joint 1 to 3 or by the dimensional constraint of the first three links. The equation which governs the boundary of W₁(4) can be obtained by solving det(G)=0, where G is the Jacobian matrix of the robot’s first three links. G is defined: [dx₄ dy₄ dz₄]^T=G[dθ₁ dθ₂ dθ₃]^T, where x₄, y₄ and z₄ are X, Y and Z coordinated of J₄.

Solving det(G)=0 then the function f₁(θ₁ θ₂ θ₃]=0 represents symbolically the W₁(4) boundary conditions.

The dexterous workspace may then be obtained by finding the hand position such that: f₁(θ₁ θ₂ θ₃]≠0 and θ_i1< θ₁< θ_i2, where i=1,2,3 are the joints.

For 6 d.o.f. robots this computation may be very difficult, the authors introduce 3 simple cases for commond practice: a PUMA type manipulator with an interesting orthogonal wrist, manipulator with a roll pitch-yaw wrist (nonintersting orthogonal wrist) and a manipulator with all unlimited joints and a roll pitch-yaw wrist and limited revolute joints.

Key Concepts

Dexterous Manipulators, Workspace Boundaries

Key Results

The PUMA type manipulator with an orthogonal wrist appears to have a spherical workspace, as already shown with different computation by Ruth. The manipulator with a roll pitch-yaw wrist (nonintersting orthogonal wrist) also appears to have spherical workspace, computations for both manipulator are reported at page 101 and 102. The manipulator with all unlimited joints and a roll pitch-yaw wrist and limited revolute joints has the difference that has to be described either by the dimensional constraint or by the rotating limit, since joint aren’t unlimited.